{
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"id": "85f49cdb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "65e72c03",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"import sys\n",
"sys.path.append('../src')\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
" \n",
"sns.set(font_scale = 3) \n",
"sns.set_theme()\n",
"sns.set_style(\"whitegrid\") \n",
"\n",
"import pandas as pd\n",
"import pickle\n",
"\n",
"import dualloop as dual_loops\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "9cf4a820",
"metadata": {},
"outputs": [],
"source": [
"def read_config(config_file):\n",
" with open(config_file, 'r') as f:\n",
" config = json.load(f)\n",
" return config\n",
"\n",
"cfg = read_config('../config.json')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "10dbeca4",
"metadata": {},
"outputs": [],
"source": [
"def plot_f1_result(results, dataset_name): \n",
" exp_result_df = pd.DataFrame(results)\n",
"\n",
" fig, ax = plt.subplots(figsize=(10, 8)) \n",
" plt.ylim(0, 100)\n",
"\n",
" p = sns.lineplot(x='iteration', y='metric', hue='methods', ax=ax, data=exp_result_df, \n",
" style=\"methods\", markers=True)\n",
"\n",
" p.set_xlabel(\"# of queries for learning\")\n",
" p.set_ylabel(\"F1 (%)\") \n",
" \n",
" ax.title.set_text(dataset_name)\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "6bcf12d6",
"metadata": {},
"outputs": [],
"source": [
"def run_experiment(cfg, dataset_name, method_name, test_case):\n",
" my_dataset_df = pd.read_csv('../data/csv/' + dataset_name + '_matrix.csv')\n",
"\n",
" lfs_set = cfg['lfs_set']\n",
" feature_set = cfg['feature_set']\n",
" methods = cfg['methods']\n",
" method_config = methods[method_name]\n",
"\n",
" epochs = 100\n",
" balance = [0.9, 0.1]\n",
"\n",
" total_size = len(my_dataset_df) \n",
" \n",
" num_iteration = int(total_size * 0.2) # explore only the first 20% of the dataset\n",
" if num_iteration > 250:\n",
" num_iteration = 250\n",
"\n",
" if dataset_name.startswith('conference-'):\n",
" batch_size = 10\n",
" interval_slow_loop = 20\n",
" elif dataset_name.startswith('ai4eu-'):\n",
" batch_size = 50\n",
" interval_slow_loop = 100\n",
" elif dataset_name.startswith('nasa-'):\n",
" batch_size = 100\n",
" interval_slow_loop = 200\n",
" elif dataset_name.startswith('anatomy-'):\n",
" batch_size = 200\n",
" interval_slow_loop = 500\n",
" else:\n",
" batch_size = 100\n",
" interval_slow_loop = 200\n",
"\n",
" result = dual_loops.run_experiment(method_config, my_dataset_df, lfs_set, feature_set,\n",
" total_size, num_iteration, interval_slow_loop, batch_size,\n",
" balance, epochs, False)\n",
"\n",
" return result\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "08636490",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"no selection of lfs due to limited number of annotated samples\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "550e601586be4335906891d86dd50433",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/250 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0.5923076923076923, 0.5923076923076923, 0.1, 0.20588235294117646, 0.5727272727272728, 0.5923076923076923, 0.5923076923076923, 0.182, 0.182, 0.1, 0.1, 0.1, 0.5499999999999999, 0.5384615384615384, 0.1]\n",
"[0.5923076923076923, 0.5923076923076923, 0.1, 0.20588235294117646, 0.5727272727272728, 0.5923076923076923, 0.5923076923076923, 0.098, 0.098, 0.1, 0.1, 0.1, 0.5499999999999999, 0.5384615384615384, 0.1]\n",
"========= SLOW LOOP ==============\n",
"===== LF_class_name_similarity_ma =========\n",
"x0 [array([0.82135352])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.82135352])], 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 609\n",
"-0.08210180623973727\n",
"[0.82135352] -0.08210180623973727 14 {'x0': array([0.82135352]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006643635397289397\n",
"[0.37432669] -0.006643635397289397 14 {'x0': array([0.37432669]), 'annotated': {'tp': 14, 'fp': 86, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7526, 'tn': 93, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009877518767285659\n",
"[0.60567331] -0.009877518767285659 14 {'x0': array([0.60567331]), 'annotated': {'tp': 14, 'fp': 84, 'tn': 2, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5062, 'tn': 2557, 'fn': 0, 'coverage': 1.0}}\n",
"-0.024715768660405337\n",
"[0.74865338] -0.024715768660405337 14 {'x0': array([0.74865338]), 'annotated': {'tp': 14, 'fp': 66, 'tn': 20, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2023, 'tn': 5596, 'fn': 0, 'coverage': 1.0}}\n",
"0.8743718592964824\n",
"[0.83701993] 0.8743718592964824 14 {'x0': array([0.83701993]), 'annotated': {'tp': 13, 'fp': 26, 'tn': 60, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 398, 'tn': 7221, 'fn': 0, 'coverage': 1.0}}\n",
"-0.015743073047858942\n",
"[0.69403985] -0.015743073047858942 14 {'x0': array([0.69403985]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3176, 'tn': 4443, 'fn': 0, 'coverage': 1.0}}\n",
"-0.038109756097560975\n",
"[0.7824064] -0.038109756097560975 14 {'x0': array([0.7824064]), 'annotated': {'tp': 14, 'fp': 58, 'tn': 28, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1312, 'tn': 6307, 'fn': 0, 'coverage': 1.0}}\n",
"-0.05359056806002144\n",
"[0.80326691] -0.05359056806002144 14 {'x0': array([0.80326691]), 'annotated': {'tp': 14, 'fp': 48, 'tn': 38, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 933, 'tn': 6686, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07183908045977011\n",
"[0.81615942] -0.07183908045977011 14 {'x0': array([0.81615942]), 'annotated': {'tp': 14, 'fp': 45, 'tn': 41, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 696, 'tn': 6923, 'fn': 0, 'coverage': 1.0}}\n",
"0.9105545617173524\n",
"[0.82412742] 0.9105545617173524 14 {'x0': array([0.82412742]), 'annotated': {'tp': 13, 'fp': 40, 'tn': 46, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 559, 'tn': 7060, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06402048655569782\n",
"[0.81123492] -0.06402048655569782 14 {'x0': array([0.81123492]), 'annotated': {'tp': 14, 'fp': 45, 'tn': 41, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 781, 'tn': 6838, 'fn': 0, 'coverage': 1.0}}\n",
"-0.078125\n",
"[0.81920292] -0.078125 14 {'x0': array([0.81920292]), 'annotated': {'tp': 14, 'fp': 44, 'tn': 42, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 640, 'tn': 6979, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08183306055646482\n",
"[0.82108391] -0.08183306055646482 14 {'x0': array([0.82108391]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 611, 'tn': 7008, 'fn': 0, 'coverage': 1.0}}\n",
"0.9161073825503355\n",
"[0.82224643] 0.9161073825503355 14 {'x0': array([0.82224643]), 'annotated': {'tp': 13, 'fp': 41, 'tn': 45, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 596, 'tn': 7023, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08051529790660225\n",
"[0.82036544] -0.08051529790660225 14 {'x0': array([0.82036544]), 'annotated': {'tp': 14, 'fp': 42, 'tn': 44, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 621, 'tn': 6998, 'fn': 0, 'coverage': 1.0}}\n",
"0.9174917491749175\n",
"[0.82152796] 0.9174917491749175 14 {'x0': array([0.82152796]), 'annotated': {'tp': 13, 'fp': 41, 'tn': 45, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08116883116883117\n",
"[0.82080948] -0.08116883116883117 14 {'x0': array([0.82080948]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 616, 'tn': 7003, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08210180623973727\n",
"[0.82125352] -0.08210180623973727 14 {'x0': array([0.82125352]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08210180623973727\n",
"[0.82135835] -0.08210180623973727 14 {'x0': array([0.82135835]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"0.9178981937602627\n",
"[0.82139168] 0.9178981937602627 14 {'x0': array([0.82139168]), 'annotated': {'tp': 13, 'fp': 41, 'tn': 45, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08210180623973727\n",
"[0.82131831] -0.08210180623973727 14 {'x0': array([0.82131831]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4644348621368408 s\n",
" direc: array([[1.]])\n",
" fun: -0.08210180623973727\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.82131831])\n",
"new x0 = [0.82131831]\n",
"NEW Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 609, 'tn': 7010, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_class_name_similarity_ma_tuned\n",
"===== LF_class_name_similarity_mb =========\n",
"x0 [array([0.45200763])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 606\n",
"-0.08250825082508251\n",
"[0.45200763] -0.08250825082508251 14 {'x0': array([0.45200763]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"-0.045413260672116255\n",
"[0.37432669] -0.045413260672116255 14 {'x0': array([0.37432669]), 'annotated': {'tp': 14, 'fp': 23, 'tn': 63, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1101, 'tn': 6518, 'fn': 0, 'coverage': 1.0}}\n",
"1.7311827956989247\n",
"[0.60567331] 1.7311827956989247 14 {'x0': array([0.60567331]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 79, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 186, 'tn': 7433, 'fn': 0, 'coverage': 1.0}}\n",
"-0.017562346329469618\n",
"[0.23134662] -0.017562346329469618 14 {'x0': array([0.23134662]), 'annotated': {'tp': 14, 'fp': 65, 'tn': 21, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2847, 'tn': 4772, 'fn': 0, 'coverage': 1.0}}\n",
"-0.028328611898016998\n",
"[0.30746665] -0.028328611898016998 14 {'x0': array([0.30746665]), 'annotated': {'tp': 14, 'fp': 44, 'tn': 42, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1765, 'tn': 5854, 'fn': 0, 'coverage': 1.0}}\n",
"0.9089253187613844\n",
"[0.46269324] 0.9089253187613844 14 {'x0': array([0.46269324]), 'annotated': {'tp': 13, 'fp': 14, 'tn': 72, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 549, 'tn': 7070, 'fn': 0, 'coverage': 1.0}}\n",
"-0.05747126436781609\n",
"[0.40807971] -0.05747126436781609 14 {'x0': array([0.40807971]), 'annotated': {'tp': 14, 'fp': 21, 'tn': 65, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 870, 'tn': 6749, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06830601092896176\n",
"[0.42894022] -0.06830601092896176 14 {'x0': array([0.42894022]), 'annotated': {'tp': 14, 'fp': 20, 'tn': 66, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 732, 'tn': 6887, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07621951219512195\n",
"[0.44183272] -0.07621951219512195 14 {'x0': array([0.44183272]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 656, 'tn': 6963, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.08077544426494346\n",
"[0.44980073] -0.08077544426494346 14 {'x0': array([0.44980073]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 619, 'tn': 7000, 'fn': 0, 'coverage': 1.0}}\n",
"0.9152542372881356\n",
"[0.45472523] 0.9152542372881356 14 {'x0': array([0.45472523]), 'annotated': {'tp': 13, 'fp': 15, 'tn': 71, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 590, 'tn': 7029, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07936507936507936\n",
"[0.44675722] -0.07936507936507936 14 {'x0': array([0.44675722]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 630, 'tn': 6989, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08223684210526316\n",
"[0.45168172] -0.08223684210526316 14 {'x0': array([0.45168172]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 608, 'tn': 7011, 'fn': 0, 'coverage': 1.0}}\n",
"0.9170812603648425\n",
"[0.45284424] 0.9170812603648425 14 {'x0': array([0.45284424]), 'annotated': {'tp': 13, 'fp': 15, 'tn': 71, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 603, 'tn': 7016, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08143322475570032\n",
"[0.45096325] -0.08143322475570032 14 {'x0': array([0.45096325]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 614, 'tn': 7005, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08250825082508251\n",
"[0.45212576] -0.08250825082508251 14 {'x0': array([0.45212576]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"0.9170812603648425\n",
"[0.4526041] 0.9170812603648425 14 {'x0': array([0.4526041]), 'annotated': {'tp': 13, 'fp': 15, 'tn': 71, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 603, 'tn': 7016, 'fn': 0, 'coverage': 1.0}}\n",
"0.9173553719008265\n",
"[0.45230847] 0.9173553719008265 14 {'x0': array([0.45230847]), 'annotated': {'tp': 13, 'fp': 15, 'tn': 71, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 605, 'tn': 7014, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08250825082508251\n",
"[0.45195615] -0.08250825082508251 14 {'x0': array([0.45195615]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08250825082508251\n",
"[0.45204096] -0.08250825082508251 14 {'x0': array([0.45204096]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08250825082508251\n",
"[0.45200763] -0.08250825082508251 14 {'x0': array([0.45200763]), 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4782052040100098 s\n",
" direc: array([[1.]])\n",
" fun: -0.08250825082508251\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.45200763])\n",
"new x0 = [0.45200763]\n",
"NEW Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 14, 'fp': 15, 'tn': 71, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 606, 'tn': 7013, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_class_name_similarity_mb_tuned\n",
"===== LF_label_similarity_ma =========\n",
"x0 [array([0.8213558])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.8213558])], 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 548\n",
"-0.09124087591240876\n",
"[0.8213558] -0.09124087591240876 14 {'x0': array([0.8213558]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006712310377231843\n",
"[0.37432669] -0.006712310377231843 14 {'x0': array([0.37432669]), 'annotated': {'tp': 14, 'fp': 86, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7449, 'tn': 170, 'fn': 0, 'coverage': 1.0}}\n",
"-0.01049097775912715\n",
"[0.60567331] -0.01049097775912715 14 {'x0': array([0.60567331]), 'annotated': {'tp': 14, 'fp': 84, 'tn': 2, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4766, 'tn': 2853, 'fn': 0, 'coverage': 1.0}}\n",
"-0.027307482250136537\n",
"[0.74865338] -0.027307482250136537 14 {'x0': array([0.74865338]), 'annotated': {'tp': 14, 'fp': 65, 'tn': 21, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1831, 'tn': 5788, 'fn': 0, 'coverage': 1.0}}\n",
"0.8599439775910365\n",
"[0.83701993] 0.8599439775910365 14 {'x0': array([0.83701993]), 'annotated': {'tp': 13, 'fp': 22, 'tn': 64, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 357, 'tn': 7262, 'fn': 0, 'coverage': 1.0}}\n",
"-0.01721170395869191\n",
"[0.69403985] -0.01721170395869191 14 {'x0': array([0.69403985]), 'annotated': {'tp': 14, 'fp': 75, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2905, 'tn': 4714, 'fn': 0, 'coverage': 1.0}}\n",
"-0.04258943781942078\n",
"[0.7824064] -0.04258943781942078 14 {'x0': array([0.7824064]), 'annotated': {'tp': 14, 'fp': 55, 'tn': 31, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1174, 'tn': 6445, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06053268765133172\n",
"[0.80326691] -0.06053268765133172 14 {'x0': array([0.80326691]), 'annotated': {'tp': 14, 'fp': 44, 'tn': 42, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 826, 'tn': 6793, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08051529790660225\n",
"[0.81615942] -0.08051529790660225 14 {'x0': array([0.81615942]), 'annotated': {'tp': 14, 'fp': 40, 'tn': 46, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 621, 'tn': 6998, 'fn': 0, 'coverage': 1.0}}\n",
"0.9001996007984032\n",
"[0.82412742] 0.9001996007984032 14 {'x0': array([0.82412742]), 'annotated': {'tp': 13, 'fp': 36, 'tn': 50, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 501, 'tn': 7118, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07215007215007214\n",
"[0.81123492] -0.07215007215007214 14 {'x0': array([0.81123492]), 'annotated': {'tp': 14, 'fp': 41, 'tn': 45, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 693, 'tn': 6926, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08695652173913043\n",
"[0.81920292] -0.08695652173913043 14 {'x0': array([0.81920292]), 'annotated': {'tp': 14, 'fp': 39, 'tn': 47, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 575, 'tn': 7044, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09090909090909091\n",
"[0.82108391] -0.09090909090909091 14 {'x0': array([0.82108391]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 550, 'tn': 7069, 'fn': 0, 'coverage': 1.0}}\n",
"0.9063670411985019\n",
"[0.82224643] 0.9063670411985019 14 {'x0': array([0.82224643]), 'annotated': {'tp': 13, 'fp': 36, 'tn': 50, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 534, 'tn': 7085, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08960573476702509\n",
"[0.82036544] -0.08960573476702509 14 {'x0': array([0.82036544]), 'annotated': {'tp': 14, 'fp': 37, 'tn': 49, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 558, 'tn': 7061, 'fn': 0, 'coverage': 1.0}}\n",
"0.908256880733945\n",
"[0.82152796] 0.908256880733945 14 {'x0': array([0.82152796]), 'annotated': {'tp': 13, 'fp': 36, 'tn': 50, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 545, 'tn': 7074, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09025270758122744\n",
"[0.82080948] -0.09025270758122744 14 {'x0': array([0.82080948]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 7065, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09124087591240876\n",
"[0.82125352] -0.09124087591240876 14 {'x0': array([0.82125352]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09124087591240876\n",
"[0.82135835] -0.09124087591240876 14 {'x0': array([0.82135835]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"0.9087591240875912\n",
"[0.82139168] 0.9087591240875912 14 {'x0': array([0.82139168]), 'annotated': {'tp': 13, 'fp': 36, 'tn': 50, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09124087591240876\n",
"[0.82131831] -0.09124087591240876 14 {'x0': array([0.82131831]), 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.433556079864502 s\n",
" direc: array([[1.]])\n",
" fun: -0.09124087591240876\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.82131831])\n",
"new x0 = [0.82131831]\n",
"NEW Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 14, 'fp': 36, 'tn': 50, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 548, 'tn': 7071, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_label_similarity_ma_tuned\n",
"===== LF_label_similarity_mb =========\n",
"x0 [array([0.45200763])]\n",
"bounds [(0, 0.98)]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"OLD Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 617\n",
"-0.08103727714748785\n",
"[0.45200763] -0.08103727714748785 14 {'x0': array([0.45200763]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"-0.04363001745200698\n",
"[0.37432669] -0.04363001745200698 14 {'x0': array([0.37432669]), 'annotated': {'tp': 14, 'fp': 26, 'tn': 60, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1146, 'tn': 6473, 'fn': 0, 'coverage': 1.0}}\n",
"1.7311827956989247\n",
"[0.60567331] 1.7311827956989247 14 {'x0': array([0.60567331]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 79, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 186, 'tn': 7433, 'fn': 0, 'coverage': 1.0}}\n",
"-0.0177367860943597\n",
"[0.23134662] -0.0177367860943597 14 {'x0': array([0.23134662]), 'annotated': {'tp': 14, 'fp': 67, 'tn': 19, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2819, 'tn': 4800, 'fn': 0, 'coverage': 1.0}}\n",
"-0.027624309392265192\n",
"[0.30715293] -0.027624309392265192 14 {'x0': array([0.30715293]), 'annotated': {'tp': 14, 'fp': 48, 'tn': 38, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1810, 'tn': 5809, 'fn': 0, 'coverage': 1.0}}\n",
"0.911504424778761\n",
"[0.46269324] 0.911504424778761 14 {'x0': array([0.46269324]), 'annotated': {'tp': 13, 'fp': 12, 'tn': 74, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 565, 'tn': 7054, 'fn': 0, 'coverage': 1.0}}\n",
"-0.05518763796909492\n",
"[0.40807971] -0.05518763796909492 14 {'x0': array([0.40807971]), 'annotated': {'tp': 14, 'fp': 21, 'tn': 65, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 906, 'tn': 6713, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06631299734748011\n",
"[0.42894022] -0.06631299734748011 14 {'x0': array([0.42894022]), 'annotated': {'tp': 14, 'fp': 18, 'tn': 68, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 754, 'tn': 6865, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07451564828614009\n",
"[0.44183272] -0.07451564828614009 14 {'x0': array([0.44183272]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 671, 'tn': 6948, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07911392405063292\n",
"[0.44980073] -0.07911392405063292 14 {'x0': array([0.44980073]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 632, 'tn': 6987, 'fn': 0, 'coverage': 1.0}}\n",
"0.9166666666666666\n",
"[0.45472523] 0.9166666666666666 14 {'x0': array([0.45472523]), 'annotated': {'tp': 13, 'fp': 13, 'tn': 73, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 600, 'tn': 7019, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07776049766718507\n",
"[0.44675722] -0.07776049766718507 14 {'x0': array([0.44675722]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 643, 'tn': 6976, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08064516129032258\n",
"[0.45168172] -0.08064516129032258 14 {'x0': array([0.45168172]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 620, 'tn': 6999, 'fn': 0, 'coverage': 1.0}}\n",
"0.9183006535947712\n",
"[0.45284424] 0.9183006535947712 14 {'x0': array([0.45284424]), 'annotated': {'tp': 13, 'fp': 13, 'tn': 73, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 612, 'tn': 7007, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08\n",
"[0.45096325] -0.08 14 {'x0': array([0.45096325]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 625, 'tn': 6994, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08103727714748785\n",
"[0.45212576] -0.08103727714748785 14 {'x0': array([0.45212576]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"0.9185667752442996\n",
"[0.4524002] 0.9185667752442996 14 {'x0': array([0.4524002]), 'annotated': {'tp': 13, 'fp': 13, 'tn': 73, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 614, 'tn': 7005, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08103727714748785\n",
"[0.45195615] -0.08103727714748785 14 {'x0': array([0.45195615]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08103727714748785\n",
"[0.45204096] -0.08103727714748785 14 {'x0': array([0.45204096]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08103727714748785\n",
"[0.45200763] -0.08103727714748785 14 {'x0': array([0.45200763]), 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.3717241287231445 s\n",
" direc: array([[1.]])\n",
" fun: -0.08103727714748785\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 20\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.45200763])\n",
"new x0 = [0.45200763]\n",
"NEW Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 14, 'fp': 13, 'tn': 73, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 617, 'tn': 7002, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_label_similarity_mb_tuned\n",
"===== LF_comment_similarity_ma =========\n",
"x0 [array([0.50581576])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.50581576])], 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 5386\n",
"-0.00928332714444857\n",
"[0.50581576] -0.00928332714444857 14 {'x0': array([0.50581576]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"-0.007133685261806249\n",
"[0.37432669] -0.007133685261806249 14 {'x0': array([0.37432669]), 'annotated': {'tp': 14, 'fp': 81, 'tn': 5, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7009, 'tn': 610, 'fn': 0, 'coverage': 1.0}}\n",
"2.9863387978142075\n",
"[0.60567331] 2.9863387978142075 14 {'x0': array([0.60567331]), 'annotated': {'tp': 11, 'fp': 40, 'tn': 46, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3660, 'tn': 3959, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006680919294494923\n",
"[0.23134662] -0.006680919294494923 14 {'x0': array([0.23134662]), 'annotated': {'tp': 14, 'fp': 83, 'tn': 3, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7484, 'tn': 135, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006808278867102397\n",
"[0.30288245] -0.006808278867102397 14 {'x0': array([0.30288245]), 'annotated': {'tp': 14, 'fp': 82, 'tn': 4, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7344, 'tn': 275, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008238589553468446\n",
"[0.46269324] -0.008238589553468446 14 {'x0': array([0.46269324]), 'annotated': {'tp': 14, 'fp': 68, 'tn': 18, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6069, 'tn': 1550, 'fn': 0, 'coverage': 1.0}}\n",
"0.9903938520653218\n",
"[0.51730676] 0.9903938520653218 14 {'x0': array([0.51730676]), 'annotated': {'tp': 13, 'fp': 61, 'tn': 25, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5205, 'tn': 2414, 'fn': 0, 'coverage': 1.0}}\n",
"-0.007748334108166744\n",
"[0.42894022] -0.007748334108166744 14 {'x0': array([0.42894022]), 'annotated': {'tp': 14, 'fp': 73, 'tn': 13, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6453, 'tn': 1166, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008787346221441126\n",
"[0.48355375] -0.008787346221441126 14 {'x0': array([0.48355375]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5690, 'tn': 1929, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00903995660820828\n",
"[0.49644625] -0.00903995660820828 14 {'x0': array([0.49644625]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5531, 'tn': 2088, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009250693802035153\n",
"[0.50441426] -0.009250693802035153 14 {'x0': array([0.50441426]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5405, 'tn': 2214, 'fn': 0, 'coverage': 1.0}}\n",
"0.9906331959535406\n",
"[0.50933876] 0.9906331959535406 14 {'x0': array([0.50933876]), 'annotated': {'tp': 13, 'fp': 63, 'tn': 23, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5338, 'tn': 2281, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009154155986818015\n",
"[0.50137075] -0.009154155986818015 14 {'x0': array([0.50137075]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5462, 'tn': 2157, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.9907028635180365\n",
"[0.50629525] 0.9907028635180365 14 {'x0': array([0.50629525]), 'annotated': {'tp': 13, 'fp': 63, 'tn': 23, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5378, 'tn': 2241, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009223390518354546\n",
"[0.50325174] -0.009223390518354546 14 {'x0': array([0.50325174]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5421, 'tn': 2198, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00927643784786642\n",
"[0.50513273] -0.00927643784786642 14 {'x0': array([0.50513273]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5390, 'tn': 2229, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009281603861147207\n",
"[0.50557678] -0.009281603861147207 14 {'x0': array([0.50557678]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5387, 'tn': 2232, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009281603861147207\n",
"[0.50563422] -0.009281603861147207 14 {'x0': array([0.50563422]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5387, 'tn': 2232, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009281603861147207\n",
"[0.50566756] -0.009281603861147207 14 {'x0': array([0.50566756]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5387, 'tn': 2232, 'fn': 0, 'coverage': 1.0}}\n",
"0.9907166728555514\n",
"[0.50590731] 0.9907166728555514 14 {'x0': array([0.50590731]), 'annotated': {'tp': 13, 'fp': 63, 'tn': 23, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00928332714444857\n",
"[0.50575913] -0.00928332714444857 14 {'x0': array([0.50575913]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00928332714444857\n",
"[0.50581573] -0.00928332714444857 14 {'x0': array([0.50581573]), 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"0.9907166728555514\n",
"[0.50584907] 0.9907166728555514 14 {'x0': array([0.50584907]), 'annotated': {'tp': 13, 'fp': 63, 'tn': 23, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.5661609172821045 s\n",
" direc: array([[1.]])\n",
" fun: -0.00928332714444857\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 23\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.50581573])\n",
"new x0 = [0.50581573]\n",
"NEW Performance: {'x0': [array([0.50581573])], 'annotated': {'tp': 14, 'fp': 63, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5386, 'tn': 2233, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_comment_similarity_ma_tuned\n",
"===== LF_comment_similarity_mb =========\n",
"x0 [array([0.14427887])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.14427887])], 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 5208\n",
"-0.009600614439324117\n",
"[0.14427887] -0.009600614439324117 14 {'x0': array([0.14427887]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"5.964311206281228\n",
"[0.37432669] 5.964311206281228 14 {'x0': array([0.37432669]), 'annotated': {'tp': 8, 'fp': 29, 'tn': 57, 'fn': 6, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1401, 'tn': 6218, 'fn': 0, 'coverage': 1.0}}\n",
"11.253731343283581\n",
"[0.60567331] 11.253731343283581 14 {'x0': array([0.60567331]), 'annotated': {'tp': 2, 'fp': 2, 'tn': 84, 'fn': 12, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 67, 'tn': 7552, 'fn': 0, 'coverage': 1.0}}\n",
"1.9864351600651113\n",
"[0.23134662] 1.9864351600651113 14 {'x0': array([0.23134662]), 'annotated': {'tp': 12, 'fp': 63, 'tn': 23, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3686, 'tn': 3933, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009534706331045004\n",
"[0.14298007] -0.009534706331045004 14 {'x0': array([0.14298007]), 'annotated': {'tp': 14, 'fp': 77, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5244, 'tn': 2375, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008187326019322089\n",
"[0.08836654] -0.008187326019322089 14 {'x0': array([0.08836654]), 'annotated': {'tp': 14, 'fp': 79, 'tn': 7, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6107, 'tn': 1512, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00877808988764045\n",
"[0.11575131] -0.00877808988764045 14 {'x0': array([0.11575131]), 'annotated': {'tp': 14, 'fp': 78, 'tn': 8, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5696, 'tn': 1923, 'fn': 0, 'coverage': 1.0}}\n",
"0.9892634743397036\n",
"[0.17673309] 0.9892634743397036 14 {'x0': array([0.17673309]), 'annotated': {'tp': 13, 'fp': 75, 'tn': 11, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4657, 'tn': 2962, 'fn': 0, 'coverage': 1.0}}\n",
"0.9900398406374502\n",
"[0.15587258] 0.9900398406374502 14 {'x0': array([0.15587258]), 'annotated': {'tp': 13, 'fp': 76, 'tn': 10, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5020, 'tn': 2599, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009177679882525698\n",
"[0.13257961] -0.009177679882525698 14 {'x0': array([0.13257961]), 'annotated': {'tp': 14, 'fp': 77, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5448, 'tn': 2171, 'fn': 0, 'coverage': 1.0}}\n",
"0.9902818270165209\n",
"[0.14790457] 0.9902818270165209 14 {'x0': array([0.14790457]), 'annotated': {'tp': 13, 'fp': 76, 'tn': 10, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5145, 'tn': 2474, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009410878976096368\n",
"[0.13900745] -0.009410878976096368 14 {'x0': array([0.13900745]), 'annotated': {'tp': 14, 'fp': 77, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5313, 'tn': 2306, 'fn': 0, 'coverage': 1.0}}\n",
"0.990395697272378\n",
"[0.14486106] 0.990395697272378 14 {'x0': array([0.14486106]), 'annotated': {'tp': 13, 'fp': 76, 'tn': 10, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5206, 'tn': 2413, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00948586605957124\n",
"[0.14146267] -0.00948586605957124 14 {'x0': array([0.14146267]), 'annotated': {'tp': 14, 'fp': 77, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5271, 'tn': 2348, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009574875526618154\n",
"[0.14369855] -0.009574875526618154 14 {'x0': array([0.14369855]), 'annotated': {'tp': 14, 'fp': 77, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5222, 'tn': 2397, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009593246354566385\n",
"[0.14414259] -0.009593246354566385 14 {'x0': array([0.14414259]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5212, 'tn': 2407, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009600614439324117\n",
"[0.14441702] -0.009600614439324117 14 {'x0': array([0.14441702]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"0.9903993855606759\n",
"[0.14458663] 0.9903993855606759 14 {'x0': array([0.14458663]), 'annotated': {'tp': 13, 'fp': 76, 'tn': 10, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009600614439324117\n",
"[0.1443122] -0.009600614439324117 14 {'x0': array([0.1443122]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009600614439324117\n",
"[0.14427887] -0.009600614439324117 14 {'x0': array([0.14427887]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009596928982725527\n",
"[0.14422681] -0.009596928982725527 14 {'x0': array([0.14422681]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5210, 'tn': 2409, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4144630432128906 s\n",
" direc: array([[1.]])\n",
" fun: -0.009600614439324117\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.14427887])\n",
"new x0 = [0.14427887]\n",
"NEW Performance: {'x0': [array([0.14427887])], 'annotated': {'tp': 14, 'fp': 76, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5208, 'tn': 2411, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_comment_similarity_mb_tuned\n",
"===== LF_random_forest_prob =========\n",
"x0 [array([0.37437816])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.37437816])], 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 0\n",
"updated boundary [(0, array([0.35437816]))]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"[0.35437816] 0 14 {'x0': array([0.35437816]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13536041] -50.0 14 {'x0': array([0.13536041]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"0\n",
"[0.21901775] 0 14 {'x0': array([0.21901775]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08365734] -50.0 14 {'x0': array([0.08365734]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.10950887] -50.0 14 {'x0': array([0.10950887]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.09963446] -50.0 14 {'x0': array([0.09963446]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.09353174] -50.0 14 {'x0': array([0.09353174]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08976006] -50.0 14 {'x0': array([0.08976006]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08742902] -50.0 14 {'x0': array([0.08742902]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08598837] -50.0 14 {'x0': array([0.08598837]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08509799] -50.0 14 {'x0': array([0.08509799]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08454771] -50.0 14 {'x0': array([0.08454771]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08420762] -50.0 14 {'x0': array([0.08420762]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08399743] -50.0 14 {'x0': array([0.08399743]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08386752] -50.0 14 {'x0': array([0.08386752]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08378724] -50.0 14 {'x0': array([0.08378724]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08373762] -50.0 14 {'x0': array([0.08373762]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08370428] -50.0 14 {'x0': array([0.08370428]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006562541015881349\n",
"[-0.18696959] -0.006562541015881349 14 {'x0': array([-0.18696959]), 'annotated': {'tp': 14, 'fp': 86, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7619, 'tn': 0, 'fn': 0, 'coverage': 1.0}}\n",
"0\n",
"[0.21901775] 0 14 {'x0': array([0.21901775]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13536041] -50.0 14 {'x0': array([0.13536041]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08365734] -50.0 14 {'x0': array([0.08365734]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.10950887] -50.0 14 {'x0': array([0.10950887]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.11938328] -50.0 14 {'x0': array([0.11938328]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.125486] -50.0 14 {'x0': array([0.125486]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.12925769] -50.0 14 {'x0': array([0.12925769]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13158872] -50.0 14 {'x0': array([0.13158872]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13302938] -50.0 14 {'x0': array([0.13302938]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13391976] -50.0 14 {'x0': array([0.13391976]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13447004] -50.0 14 {'x0': array([0.13447004]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13481013] -50.0 14 {'x0': array([0.13481013]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13502032] -50.0 14 {'x0': array([0.13502032]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13515022] -50.0 14 {'x0': array([0.13515022]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13523051] -50.0 14 {'x0': array([0.13523051]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13528013] -50.0 14 {'x0': array([0.13528013]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13531079] -50.0 14 {'x0': array([0.13531079]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13532975] -50.0 14 {'x0': array([0.13532975]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13534146] -50.0 14 {'x0': array([0.13534146]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13535048] -50.0 14 {'x0': array([0.13535048]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.13536041] -50.0 14 {'x0': array([0.13536041]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"0\n",
"[0.21901775] 0 14 {'x0': array([0.21901775]), 'annotated': {'tp': 14, 'fp': 2, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08365734] -50.0 14 {'x0': array([0.08365734]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.10950887] -50.0 14 {'x0': array([0.10950887]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-50.0\n",
"[0.09963446] -50.0 14 {'x0': array([0.09963446]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.09353174] -50.0 14 {'x0': array([0.09353174]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08976006] -50.0 14 {'x0': array([0.08976006]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08742902] -50.0 14 {'x0': array([0.08742902]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08598837] -50.0 14 {'x0': array([0.08598837]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08509799] -50.0 14 {'x0': array([0.08509799]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08454771] -50.0 14 {'x0': array([0.08454771]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08420762] -50.0 14 {'x0': array([0.08420762]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08399743] -50.0 14 {'x0': array([0.08399743]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08386752] -50.0 14 {'x0': array([0.08386752]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08378724] -50.0 14 {'x0': array([0.08378724]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08373762] -50.0 14 {'x0': array([0.08373762]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08370695] -50.0 14 {'x0': array([0.08370695]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.083688] -50.0 14 {'x0': array([0.083688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08367629] -50.0 14 {'x0': array([0.08367629]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08366905] -50.0 14 {'x0': array([0.08366905]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08366457] -50.0 14 {'x0': array([0.08366457]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08366181] -50.0 14 {'x0': array([0.08366181]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-50.0\n",
"[0.08366009] -50.0 14 {'x0': array([0.08366009]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 4.196748971939087 s\n",
" direc: array([[0.0516462]])\n",
" fun: -50.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 62\n",
" nit: 2\n",
" status: 0\n",
" success: True\n",
" x: array([0.08366009])\n",
"new x0 = [0.08366009]\n",
"NEW Performance: {'x0': [array([0.08366009])], 'annotated': {'tp': 14, 'fp': 3, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_random_forest_prob_tuned\n",
"===== LF_logistic_regression_prob =========\n",
"x0 [array([0.06936772])]\n",
"bounds [(0, array([0.15272603]))]\n",
"OLD Performance: {'x0': [array([0.06936772])], 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 8, 'tn': 7611, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 8\n",
"-3.25\n",
"[0.06936772] -3.25 14 {'x0': array([0.06936772]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 8, 'tn': 7611, 'fn': 0, 'coverage': 1.0}}\n",
"-2.5555555555555554\n",
"[0.05833615] -2.5555555555555554 14 {'x0': array([0.05833615]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 9, 'tn': 7610, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09438988] -7.0 14 {'x0': array([0.09438988]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667231] -7.0 14 {'x0': array([0.11667231]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.10553109] -7.0 14 {'x0': array([0.10553109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.10127553] -7.0 14 {'x0': array([0.10127553]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09864544] -7.0 14 {'x0': array([0.09864544]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09701996] -7.0 14 {'x0': array([0.09701996]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09601536] -7.0 14 {'x0': array([0.09601536]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09539448] -7.0 14 {'x0': array([0.09539448]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09501076] -7.0 14 {'x0': array([0.09501076]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.0947736] -7.0 14 {'x0': array([0.0947736]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09462703] -7.0 14 {'x0': array([0.09462703]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09453645] -7.0 14 {'x0': array([0.09453645]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09448046] -7.0 14 {'x0': array([0.09448046]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09444586] -7.0 14 {'x0': array([0.09444586]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.119524] -7.0 14 {'x0': array([0.119524]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-2.5555555555555554\n",
"[0.05833615] -2.5555555555555554 14 {'x0': array([0.05833615]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 9, 'tn': 7610, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09438988] -7.0 14 {'x0': array([0.09438988]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667231] -7.0 14 {'x0': array([0.11667231]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-7.0\n",
"[0.10553109] -7.0 14 {'x0': array([0.10553109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.10127553] -7.0 14 {'x0': array([0.10127553]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09864544] -7.0 14 {'x0': array([0.09864544]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09701996] -7.0 14 {'x0': array([0.09701996]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09601536] -7.0 14 {'x0': array([0.09601536]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09539448] -7.0 14 {'x0': array([0.09539448]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09501076] -7.0 14 {'x0': array([0.09501076]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.0947736] -7.0 14 {'x0': array([0.0947736]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09462703] -7.0 14 {'x0': array([0.09462703]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09453645] -7.0 14 {'x0': array([0.09453645]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09448046] -7.0 14 {'x0': array([0.09448046]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09444586] -7.0 14 {'x0': array([0.09444586]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09442448] -7.0 14 {'x0': array([0.09442448]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09441126] -7.0 14 {'x0': array([0.09441126]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09440309] -7.0 14 {'x0': array([0.09440309]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09439805] -7.0 14 {'x0': array([0.09439805]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09439493] -7.0 14 {'x0': array([0.09439493]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.094393] -7.0 14 {'x0': array([0.094393]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09439181] -7.0 14 {'x0': array([0.09439181]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09439097] -7.0 14 {'x0': array([0.09439097]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.09438988] -7.0 14 {'x0': array([0.09438988]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-2.5555555555555554\n",
"[0.05833615] -2.5555555555555554 14 {'x0': array([0.05833615]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 9, 'tn': 7610, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667231] -7.0 14 {'x0': array([0.11667231]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.10553109] -7.0 14 {'x0': array([0.10553109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.10978666] -7.0 14 {'x0': array([0.10978666]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11241674] -7.0 14 {'x0': array([0.11241674]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11404222] -7.0 14 {'x0': array([0.11404222]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11504682] -7.0 14 {'x0': array([0.11504682]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.1156677] -7.0 14 {'x0': array([0.1156677]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11605143] -7.0 14 {'x0': array([0.11605143]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11628858] -7.0 14 {'x0': array([0.11628858]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11643515] -7.0 14 {'x0': array([0.11643515]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11652574] -7.0 14 {'x0': array([0.11652574]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11658172] -7.0 14 {'x0': array([0.11658172]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11661632] -7.0 14 {'x0': array([0.11661632]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11663771] -7.0 14 {'x0': array([0.11663771]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11665092] -7.0 14 {'x0': array([0.11665092]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11665909] -7.0 14 {'x0': array([0.11665909]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11666414] -7.0 14 {'x0': array([0.11666414]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11666726] -7.0 14 {'x0': array([0.11666726]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11666919] -7.0 14 {'x0': array([0.11666919]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667038] -7.0 14 {'x0': array([0.11667038]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667111] -7.0 14 {'x0': array([0.11667111]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-7.0\n",
"[0.11667157] -7.0 14 {'x0': array([0.11667157]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667185] -7.0 14 {'x0': array([0.11667185]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667202] -7.0 14 {'x0': array([0.11667202]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667213] -7.0 14 {'x0': array([0.11667213]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.1166722] -7.0 14 {'x0': array([0.1166722]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667224] -7.0 14 {'x0': array([0.11667224]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667226] -7.0 14 {'x0': array([0.11667226]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667228] -7.0 14 {'x0': array([0.11667228]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.11667229] -7.0 14 {'x0': array([0.11667229]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.1166723] -7.0 14 {'x0': array([0.1166723]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.1166723] -7.0 14 {'x0': array([0.1166723]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.1166723] -7.0 14 {'x0': array([0.1166723]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 5.12993311882019 s\n",
" direc: array([[-5.48923112e-05]])\n",
" fun: -7.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 75\n",
" nit: 2\n",
" status: 0\n",
" success: True\n",
" x: array([0.1166723])\n",
"new x0 = [0.1166723]\n",
"NEW Performance: {'x0': [array([0.1166723])], 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7614, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_logistic_regression_prob_tuned\n",
"===== LF_xgboost_prob =========\n",
"x0 [array([0.37437816])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.37437816])], 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 1\n",
"-49.0\n",
"[0.37437816] -49.0 14 {'x0': array([0.37437816]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.37432669] -49.0 14 {'x0': array([0.37432669]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"3\n",
"[0.60567331] 3 14 {'x0': array([0.60567331]), 'annotated': {'tp': 11, 'fp': 1, 'tn': 85, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23134662] -49.0 14 {'x0': array([0.23134662]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.30283665] -49.0 14 {'x0': array([0.30283665]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.27552989] -49.0 14 {'x0': array([0.27552989]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.25865338] -49.0 14 {'x0': array([0.25865338]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.24822313] -49.0 14 {'x0': array([0.24822313]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.24177687] -49.0 14 {'x0': array([0.24177687]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23779287] -49.0 14 {'x0': array([0.23779287]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23533062] -49.0 14 {'x0': array([0.23533062]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23380887] -49.0 14 {'x0': array([0.23380887]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23286837] -49.0 14 {'x0': array([0.23286837]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23228711] -49.0 14 {'x0': array([0.23228711]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23192788] -49.0 14 {'x0': array([0.23192788]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23170586] -49.0 14 {'x0': array([0.23170586]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23156864] -49.0 14 {'x0': array([0.23156864]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23148383] -49.0 14 {'x0': array([0.23148383]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23143142] -49.0 14 {'x0': array([0.23143142]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-49.0\n",
"[0.23139809] -49.0 14 {'x0': array([0.23139809]), 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.3704888820648193 s\n",
" direc: array([[1.]])\n",
" fun: -49.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 20\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.23139809])\n",
"new x0 = [0.23139809]\n",
"NEW Performance: {'x0': [array([0.23139809])], 'annotated': {'tp': 13, 'fp': 2, 'tn': 84, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_xgboost_prob_tuned\n",
"===== LF_mlp_prob =========\n",
"x0 [array([0.08390907])]\n",
"bounds [(0, array([0.20551486]))]\n",
"OLD Performance: {'x0': [array([0.08390907])], 'annotated': {'tp': 11, 'fp': 2, 'tn': 84, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 0\n",
"updated boundary [(0, array([0.06390907]))]\n",
"3\n",
"[0.06390907] 3 14 {'x0': array([0.06390907]), 'annotated': {'tp': 11, 'fp': 2, 'tn': 84, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-0.3333333333333335\n",
"[0.02441109] -0.3333333333333335 14 {'x0': array([0.02441109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 15, 'tn': 7604, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.03949798] -13.666666666666668 14 {'x0': array([0.03949798]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-22.0\n",
"[0.04882218] -22.0 14 {'x0': array([0.04882218]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7617, 'fn': 0, 'coverage': 1.0}}\n",
"3\n",
"[0.05458486] 3 14 {'x0': array([0.05458486]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.04526065] -13.666666666666668 14 {'x0': array([0.04526065]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102333] -47.0 14 {'x0': array([0.05102333]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05238371] -47.0 14 {'x0': array([0.05238371]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05170352] -47.0 14 {'x0': array([0.05170352]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05144371] -47.0 14 {'x0': array([0.05144371]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05128314] -47.0 14 {'x0': array([0.05128314]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0511839] -47.0 14 {'x0': array([0.0511839]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05112257] -47.0 14 {'x0': array([0.05112257]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05108466] -47.0 14 {'x0': array([0.05108466]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.03826026] -13.666666666666668 14 {'x0': array([0.03826026]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.03949798] -13.666666666666668 14 {'x0': array([0.03949798]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-0.3333333333333335\n",
"[0.02441109] -0.3333333333333335 14 {'x0': array([0.02441109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 15, 'tn': 7604, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.04882218] -22.0 14 {'x0': array([0.04882218]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7617, 'fn': 0, 'coverage': 1.0}}\n",
"3\n",
"[0.05458486] 3 14 {'x0': array([0.05458486]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.04526065] -13.666666666666668 14 {'x0': array([0.04526065]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102333] -47.0 14 {'x0': array([0.05102333]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05238371] -47.0 14 {'x0': array([0.05238371]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05170352] -47.0 14 {'x0': array([0.05170352]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05196333] -47.0 14 {'x0': array([0.05196333]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0521239] -47.0 14 {'x0': array([0.0521239]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05222314] -47.0 14 {'x0': array([0.05222314]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05228448] -47.0 14 {'x0': array([0.05228448]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05232238] -47.0 14 {'x0': array([0.05232238]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05234581] -47.0 14 {'x0': array([0.05234581]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05236029] -47.0 14 {'x0': array([0.05236029]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05236924] -47.0 14 {'x0': array([0.05236924]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05237477] -47.0 14 {'x0': array([0.05237477]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05237818] -47.0 14 {'x0': array([0.05237818]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0523803] -47.0 14 {'x0': array([0.0523803]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0523816] -47.0 14 {'x0': array([0.0523816]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05238241] -47.0 14 {'x0': array([0.05238241]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05238291] -47.0 14 {'x0': array([0.05238291]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-0.3333333333333335\n",
"[0.02441109] -0.3333333333333335 14 {'x0': array([0.02441109]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 15, 'tn': 7604, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.03949798] -13.666666666666668 14 {'x0': array([0.03949798]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.04882218] -22.0 14 {'x0': array([0.04882218]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7617, 'fn': 0, 'coverage': 1.0}}\n",
"3\n",
"[0.05458486] 3 14 {'x0': array([0.05458486]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7619, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.04526065] -13.666666666666668 14 {'x0': array([0.04526065]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7616, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102333] -47.0 14 {'x0': array([0.05102333]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05238371] -47.0 14 {'x0': array([0.05238371]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05170352] -47.0 14 {'x0': array([0.05170352]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05144371] -47.0 14 {'x0': array([0.05144371]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-47.0\n",
"[0.05128314] -47.0 14 {'x0': array([0.05128314]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0511839] -47.0 14 {'x0': array([0.0511839]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05112257] -47.0 14 {'x0': array([0.05112257]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05108466] -47.0 14 {'x0': array([0.05108466]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05106124] -47.0 14 {'x0': array([0.05106124]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05104676] -47.0 14 {'x0': array([0.05104676]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05103781] -47.0 14 {'x0': array([0.05103781]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05103228] -47.0 14 {'x0': array([0.05103228]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102886] -47.0 14 {'x0': array([0.05102886]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102675] -47.0 14 {'x0': array([0.05102675]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102544] -47.0 14 {'x0': array([0.05102544]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102464] -47.0 14 {'x0': array([0.05102464]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102414] -47.0 14 {'x0': array([0.05102414]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102383] -47.0 14 {'x0': array([0.05102383]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102364] -47.0 14 {'x0': array([0.05102364]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102352] -47.0 14 {'x0': array([0.05102352]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.05102345] -47.0 14 {'x0': array([0.05102345]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"-47.0\n",
"[0.0510234] -47.0 14 {'x0': array([0.0510234]), 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 4.371363878250122 s\n",
" direc: array([[0.00129824]])\n",
" fun: -47.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 64\n",
" nit: 2\n",
" status: 0\n",
" success: True\n",
" x: array([0.0510234])\n",
"new x0 = [0.0510234]\n",
"NEW Performance: {'x0': [array([0.0510234])], 'annotated': {'tp': 11, 'fp': 3, 'tn': 83, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1, 'tn': 7618, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_mlp_prob_tuned\n",
"LF augumentation time: 26.745141983032227 s\n",
"[0.5923076923076923, 0.5923076923076923, 0.1, 0.20588235294117646, 0.5727272727272728, 0.5923076923076923, 0.5923076923076923, 0.06533333333333333, 0.06533333333333333, 0.1, 0.1, 0.1, 0.5499999999999999, 0.5384615384615384, 0.1, 0.5499999999999999, 0.5499999999999999, 0.07050359712230216, 0.15806451612903225, 0.23902439024390243, 0.5764705882352941, 0.08672566371681416, 0.6, 0.24499999999999997, 0.6066666666666667, 0.7, 0.175, 0.5923076923076923, 0.5923076923076923]\n",
"[0.5923076923076923, 0.5923076923076923, 0.1, 0.20588235294117646, 0.5727272727272728, 0.5923076923076923, 0.5923076923076923, 0.0525, 0.0525, 0.1, 0.1, 0.1, 0.5499999999999999, 0.5384615384615384, 0.1, 0.5499999999999999, 0.4666666666666666, 0.055555555555555546, 0.09374999999999999, 0.11538461538461538, 0.5444444444444444, 0.06441717791411042, 0.6, 0.11666666666666665, 0.56875, 0.7, 0.0990566037735849, 0.5923076923076923, 0.5923076923076923]\n",
"========= SLOW LOOP ==============\n",
"===== LF_class_name_similarity_ma =========\n",
"x0 [array([0.82131831])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 552\n",
"-0.09057971014492754\n",
"[0.82131831] -0.09057971014492754 15 {'x0': array([0.82131831]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006733099919202801\n",
"[0.37432669] -0.006733099919202801 15 {'x0': array([0.37432669]), 'annotated': {'tp': 15, 'fp': 185, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7426, 'tn': 93, 'fn': 0, 'coverage': 1.0}}\n",
"-0.010058338362502514\n",
"[0.60567331] -0.010058338362502514 15 {'x0': array([0.60567331]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4971, 'tn': 2548, 'fn': 0, 'coverage': 1.0}}\n",
"-0.02556237218813906\n",
"[0.74865338] -0.02556237218813906 15 {'x0': array([0.74865338]), 'annotated': {'tp': 15, 'fp': 132, 'tn': 53, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1956, 'tn': 5563, 'fn': 0, 'coverage': 1.0}}\n",
"0.8567335243553009\n",
"[0.83701993] 0.8567335243553009 15 {'x0': array([0.83701993]), 'annotated': {'tp': 14, 'fp': 74, 'tn': 111, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 349, 'tn': 7170, 'fn': 0, 'coverage': 1.0}}\n",
"-0.016134236850596968\n",
"[0.69403985] -0.016134236850596968 15 {'x0': array([0.69403985]), 'annotated': {'tp': 15, 'fp': 152, 'tn': 33, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3099, 'tn': 4420, 'fn': 0, 'coverage': 1.0}}\n",
"-0.04006410256410257\n",
"[0.7824064] -0.04006410256410257 15 {'x0': array([0.7824064]), 'annotated': {'tp': 15, 'fp': 121, 'tn': 64, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1248, 'tn': 6271, 'fn': 0, 'coverage': 1.0}}\n",
"-0.057208237986270026\n",
"[0.80326691] -0.057208237986270026 15 {'x0': array([0.80326691]), 'annotated': {'tp': 15, 'fp': 106, 'tn': 79, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 874, 'tn': 6645, 'fn': 0, 'coverage': 1.0}}\n",
"-0.0782472613458529\n",
"[0.81615942] -0.0782472613458529 15 {'x0': array([0.81615942]), 'annotated': {'tp': 15, 'fp': 101, 'tn': 84, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 639, 'tn': 6880, 'fn': 0, 'coverage': 1.0}}\n",
"0.9007936507936508\n",
"[0.82412742] 0.9007936507936508 15 {'x0': array([0.82412742]), 'annotated': {'tp': 14, 'fp': 94, 'tn': 91, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 504, 'tn': 7015, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06915629322268327\n",
"[0.81123492] -0.06915629322268327 15 {'x0': array([0.81123492]), 'annotated': {'tp': 15, 'fp': 102, 'tn': 83, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 723, 'tn': 6796, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08576329331046312\n",
"[0.81920292] -0.08576329331046312 15 {'x0': array([0.81920292]), 'annotated': {'tp': 15, 'fp': 100, 'tn': 85, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 583, 'tn': 6936, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09025270758122744\n",
"[0.82108391] -0.09025270758122744 15 {'x0': array([0.82108391]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.9072356215213359\n",
"[0.82224643] 0.9072356215213359 15 {'x0': array([0.82224643]), 'annotated': {'tp': 14, 'fp': 97, 'tn': 88, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 539, 'tn': 6980, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08865248226950355\n",
"[0.82036544] -0.08865248226950355 15 {'x0': array([0.82036544]), 'annotated': {'tp': 15, 'fp': 98, 'tn': 87, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 564, 'tn': 6955, 'fn': 0, 'coverage': 1.0}}\n",
"0.9089253187613844\n",
"[0.82152796] 0.9089253187613844 15 {'x0': array([0.82152796]), 'annotated': {'tp': 14, 'fp': 97, 'tn': 88, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 549, 'tn': 6970, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08944543828264759\n",
"[0.82080948] -0.08944543828264759 15 {'x0': array([0.82080948]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 559, 'tn': 6960, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09057971014492754\n",
"[0.82125352] -0.09057971014492754 15 {'x0': array([0.82125352]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09057971014492754\n",
"[0.82135835] -0.09057971014492754 15 {'x0': array([0.82135835]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"0.9094202898550725\n",
"[0.82139168] 0.9094202898550725 15 {'x0': array([0.82139168]), 'annotated': {'tp': 14, 'fp': 97, 'tn': 88, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09057971014492754\n",
"[0.82131831] -0.09057971014492754 15 {'x0': array([0.82131831]), 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4769060611724854 s\n",
" direc: array([[1.]])\n",
" fun: -0.09057971014492754\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.82131831])\n",
"new x0 = [0.82131831]\n",
"NEW Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 15, 'fp': 97, 'tn': 88, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_class_name_similarity_ma_tuned\n",
"===== LF_class_name_similarity_mb =========\n",
"x0 [array([0.45200763])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 544\n",
"-0.09191176470588236\n",
"[0.45200763] -0.09191176470588236 15 {'x0': array([0.45200763]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"-0.04849660523763336\n",
"[0.37432669] -0.04849660523763336 15 {'x0': array([0.37432669]), 'annotated': {'tp': 15, 'fp': 92, 'tn': 93, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1031, 'tn': 6488, 'fn': 0, 'coverage': 1.0}}\n",
"1.6710526315789473\n",
"[0.60567331] 1.6710526315789473 15 {'x0': array([0.60567331]), 'annotated': {'tp': 13, 'fp': 40, 'tn': 145, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 152, 'tn': 7367, 'fn': 0, 'coverage': 1.0}}\n",
"-0.01818181818181818\n",
"[0.23134662] -0.01818181818181818 15 {'x0': array([0.23134662]), 'annotated': {'tp': 15, 'fp': 161, 'tn': 24, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2750, 'tn': 4769, 'fn': 0, 'coverage': 1.0}}\n",
"-0.02986857825567503\n",
"[0.30802744] -0.02986857825567503 15 {'x0': array([0.30802744]), 'annotated': {'tp': 15, 'fp': 127, 'tn': 58, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1674, 'tn': 5845, 'fn': 0, 'coverage': 1.0}}\n",
"0.8973305954825462\n",
"[0.46269324] 0.8973305954825462 15 {'x0': array([0.46269324]), 'annotated': {'tp': 14, 'fp': 75, 'tn': 110, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 487, 'tn': 7032, 'fn': 0, 'coverage': 1.0}}\n",
"-0.062421972534332085\n",
"[0.40807971] -0.062421972534332085 15 {'x0': array([0.40807971]), 'annotated': {'tp': 15, 'fp': 89, 'tn': 96, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 801, 'tn': 6718, 'fn': 0, 'coverage': 1.0}}\n",
"-0.0748502994011976\n",
"[0.42894022] -0.0748502994011976 15 {'x0': array([0.42894022]), 'annotated': {'tp': 15, 'fp': 83, 'tn': 102, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 668, 'tn': 6851, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08431703204047218\n",
"[0.44183272] -0.08431703204047218 15 {'x0': array([0.44183272]), 'annotated': {'tp': 15, 'fp': 77, 'tn': 108, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 593, 'tn': 6926, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08976660682226212\n",
"[0.44980073] -0.08976660682226212 15 {'x0': array([0.44980073]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 557, 'tn': 6962, 'fn': 0, 'coverage': 1.0}}\n",
"0.9053030303030303\n",
"[0.45472523] 0.9053030303030303 15 {'x0': array([0.45472523]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 109, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 528, 'tn': 6991, 'fn': 0, 'coverage': 1.0}}\n",
"-0.0880281690140845\n",
"[0.44675722] -0.0880281690140845 15 {'x0': array([0.44675722]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 568, 'tn': 6951, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09157509157509157\n",
"[0.45168172] -0.09157509157509157 15 {'x0': array([0.45168172]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 546, 'tn': 6973, 'fn': 0, 'coverage': 1.0}}\n",
"0.9075785582255083\n",
"[0.45284424] 0.9075785582255083 15 {'x0': array([0.45284424]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 109, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 541, 'tn': 6978, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09057971014492754\n",
"[0.45096325] -0.09057971014492754 15 {'x0': array([0.45096325]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 552, 'tn': 6967, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09191176470588236\n",
"[0.45212576] -0.09191176470588236 15 {'x0': array([0.45212576]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"0.9075785582255083\n",
"[0.4526064] 0.9075785582255083 15 {'x0': array([0.4526064]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 109, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 541, 'tn': 6978, 'fn': 0, 'coverage': 1.0}}\n",
"0.9079189686924494\n",
"[0.45230935] 0.9079189686924494 15 {'x0': array([0.45230935]), 'annotated': {'tp': 14, 'fp': 76, 'tn': 109, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 543, 'tn': 6976, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09191176470588236\n",
"[0.45195615] -0.09191176470588236 15 {'x0': array([0.45195615]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09191176470588236\n",
"[0.45204096] -0.09191176470588236 15 {'x0': array([0.45204096]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09191176470588236\n",
"[0.45200763] -0.09191176470588236 15 {'x0': array([0.45200763]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.47446608543396 s\n",
" direc: array([[1.]])\n",
" fun: -0.09191176470588236\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.45200763])\n",
"new x0 = [0.45200763]\n",
"NEW Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 544, 'tn': 6975, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_class_name_similarity_mb_tuned\n",
"===== LF_label_similarity_ma =========\n",
"x0 [array([0.82131831])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 492\n",
"-0.1016260162601626\n",
"[0.82131831] -0.1016260162601626 15 {'x0': array([0.82131831]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006803646754660498\n",
"[0.37432669] -0.006803646754660498 15 {'x0': array([0.37432669]), 'annotated': {'tp': 15, 'fp': 185, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7349, 'tn': 170, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.010690613641223007\n",
"[0.60567331] -0.010690613641223007 15 {'x0': array([0.60567331]), 'annotated': {'tp': 15, 'fp': 172, 'tn': 13, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4677, 'tn': 2842, 'fn': 0, 'coverage': 1.0}}\n",
"-0.028312570781426953\n",
"[0.74865338] -0.028312570781426953 15 {'x0': array([0.74865338]), 'annotated': {'tp': 15, 'fp': 129, 'tn': 56, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1766, 'tn': 5753, 'fn': 0, 'coverage': 1.0}}\n",
"0.8376623376623377\n",
"[0.83701993] 0.8376623376623377 15 {'x0': array([0.83701993]), 'annotated': {'tp': 14, 'fp': 70, 'tn': 115, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 308, 'tn': 7211, 'fn': 0, 'coverage': 1.0}}\n",
"-0.01765536723163842\n",
"[0.69403985] -0.01765536723163842 15 {'x0': array([0.69403985]), 'annotated': {'tp': 15, 'fp': 147, 'tn': 38, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2832, 'tn': 4687, 'fn': 0, 'coverage': 1.0}}\n",
"-0.044923629829290206\n",
"[0.7824064] -0.044923629829290206 15 {'x0': array([0.7824064]), 'annotated': {'tp': 15, 'fp': 115, 'tn': 70, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1113, 'tn': 6406, 'fn': 0, 'coverage': 1.0}}\n",
"-0.06501950585175553\n",
"[0.80326691] -0.06501950585175553 15 {'x0': array([0.80326691]), 'annotated': {'tp': 15, 'fp': 100, 'tn': 85, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 769, 'tn': 6750, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08849557522123894\n",
"[0.81615942] -0.08849557522123894 15 {'x0': array([0.81615942]), 'annotated': {'tp': 15, 'fp': 95, 'tn': 90, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 565, 'tn': 6954, 'fn': 0, 'coverage': 1.0}}\n",
"0.8878923766816144\n",
"[0.82412742] 0.8878923766816144 15 {'x0': array([0.82412742]), 'annotated': {'tp': 14, 'fp': 90, 'tn': 95, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 446, 'tn': 7073, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07849293563579278\n",
"[0.81123492] -0.07849293563579278 15 {'x0': array([0.81123492]), 'annotated': {'tp': 15, 'fp': 96, 'tn': 89, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 637, 'tn': 6882, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09633911368015415\n",
"[0.81920292] -0.09633911368015415 15 {'x0': array([0.81920292]), 'annotated': {'tp': 15, 'fp': 94, 'tn': 91, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 519, 'tn': 7000, 'fn': 0, 'coverage': 1.0}}\n",
"-0.10121457489878542\n",
"[0.82108391] -0.10121457489878542 15 {'x0': array([0.82108391]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 494, 'tn': 7025, 'fn': 0, 'coverage': 1.0}}\n",
"0.895397489539749\n",
"[0.82224643] 0.895397489539749 15 {'x0': array([0.82224643]), 'annotated': {'tp': 14, 'fp': 91, 'tn': 94, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 478, 'tn': 7041, 'fn': 0, 'coverage': 1.0}}\n",
"-0.099601593625498\n",
"[0.82036544] -0.099601593625498 15 {'x0': array([0.82036544]), 'annotated': {'tp': 15, 'fp': 92, 'tn': 93, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 502, 'tn': 7017, 'fn': 0, 'coverage': 1.0}}\n",
"0.8977505112474438\n",
"[0.82152796] 0.8977505112474438 15 {'x0': array([0.82152796]), 'annotated': {'tp': 14, 'fp': 91, 'tn': 94, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 489, 'tn': 7030, 'fn': 0, 'coverage': 1.0}}\n",
"-0.10040160642570281\n",
"[0.82080948] -0.10040160642570281 15 {'x0': array([0.82080948]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 498, 'tn': 7021, 'fn': 0, 'coverage': 1.0}}\n",
"-0.1016260162601626\n",
"[0.82125352] -0.1016260162601626 15 {'x0': array([0.82125352]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"-0.1016260162601626\n",
"[0.82135835] -0.1016260162601626 15 {'x0': array([0.82135835]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"0.8983739837398375\n",
"[0.82139168] 0.8983739837398375 15 {'x0': array([0.82139168]), 'annotated': {'tp': 14, 'fp': 91, 'tn': 94, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"-0.1016260162601626\n",
"[0.82131831] -0.1016260162601626 15 {'x0': array([0.82131831]), 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4706261157989502 s\n",
" direc: array([[1.]])\n",
" fun: -0.1016260162601626\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.82131831])\n",
"new x0 = [0.82131831]\n",
"NEW Performance: {'x0': [array([0.82131831])], 'annotated': {'tp': 15, 'fp': 91, 'tn': 94, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 492, 'tn': 7027, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_label_similarity_ma_tuned\n",
"===== LF_label_similarity_mb =========\n",
"x0 [array([0.45200763])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 554\n",
"-0.09025270758122744\n",
"[0.45200763] -0.09025270758122744 15 {'x0': array([0.45200763]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"-0.046511627906976744\n",
"[0.37432669] -0.046511627906976744 15 {'x0': array([0.37432669]), 'annotated': {'tp': 15, 'fp': 96, 'tn': 89, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1075, 'tn': 6444, 'fn': 0, 'coverage': 1.0}}\n",
"1.673202614379085\n",
"[0.60567331] 1.673202614379085 15 {'x0': array([0.60567331]), 'annotated': {'tp': 13, 'fp': 39, 'tn': 146, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 153, 'tn': 7366, 'fn': 0, 'coverage': 1.0}}\n",
"-0.018368846436443792\n",
"[0.23134662] -0.018368846436443792 15 {'x0': array([0.23134662]), 'annotated': {'tp': 15, 'fp': 163, 'tn': 22, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2722, 'tn': 4797, 'fn': 0, 'coverage': 1.0}}\n",
"-0.029069767441860465\n",
"[0.30766468] -0.029069767441860465 15 {'x0': array([0.30766468]), 'annotated': {'tp': 15, 'fp': 132, 'tn': 53, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1720, 'tn': 5799, 'fn': 0, 'coverage': 1.0}}\n",
"0.900398406374502\n",
"[0.46269324] 0.900398406374502 15 {'x0': array([0.46269324]), 'annotated': {'tp': 14, 'fp': 74, 'tn': 111, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 502, 'tn': 7017, 'fn': 0, 'coverage': 1.0}}\n",
"-0.05973715651135006\n",
"[0.40807971] -0.05973715651135006 15 {'x0': array([0.40807971]), 'annotated': {'tp': 15, 'fp': 89, 'tn': 96, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 837, 'tn': 6682, 'fn': 0, 'coverage': 1.0}}\n",
"-0.07256894049346879\n",
"[0.42894022] -0.07256894049346879 15 {'x0': array([0.42894022]), 'annotated': {'tp': 15, 'fp': 82, 'tn': 103, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 689, 'tn': 6830, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08237232289950576\n",
"[0.44183272] -0.08237232289950576 15 {'x0': array([0.44183272]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 607, 'tn': 6912, 'fn': 0, 'coverage': 1.0}}\n",
"-0.0880281690140845\n",
"[0.44980073] -0.0880281690140845 15 {'x0': array([0.44980073]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 568, 'tn': 6951, 'fn': 0, 'coverage': 1.0}}\n",
"0.9068901303538175\n",
"[0.45472523] 0.9068901303538175 15 {'x0': array([0.45472523]), 'annotated': {'tp': 14, 'fp': 75, 'tn': 110, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 537, 'tn': 6982, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08635578583765112\n",
"[0.44675722] -0.08635578583765112 15 {'x0': array([0.44675722]), 'annotated': {'tp': 15, 'fp': 76, 'tn': 109, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 579, 'tn': 6940, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08976660682226212\n",
"[0.45168172] -0.08976660682226212 15 {'x0': array([0.45168172]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 557, 'tn': 6962, 'fn': 0, 'coverage': 1.0}}\n",
"0.9089253187613844\n",
"[0.45284424] 0.9089253187613844 15 {'x0': array([0.45284424]), 'annotated': {'tp': 14, 'fp': 75, 'tn': 110, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 549, 'tn': 6970, 'fn': 0, 'coverage': 1.0}}\n",
"-0.08896797153024912\n",
"[0.45096325] -0.08896797153024912 15 {'x0': array([0.45096325]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 562, 'tn': 6957, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09025270758122744\n",
"[0.45212576] -0.09025270758122744 15 {'x0': array([0.45212576]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"0.9092558983666061\n",
"[0.4524002] 0.9092558983666061 15 {'x0': array([0.4524002]), 'annotated': {'tp': 14, 'fp': 75, 'tn': 110, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 551, 'tn': 6968, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.09025270758122744\n",
"[0.45195615] -0.09025270758122744 15 {'x0': array([0.45195615]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09025270758122744\n",
"[0.45204096] -0.09025270758122744 15 {'x0': array([0.45204096]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"-0.09025270758122744\n",
"[0.45200763] -0.09025270758122744 15 {'x0': array([0.45200763]), 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.3770971298217773 s\n",
" direc: array([[1.]])\n",
" fun: -0.09025270758122744\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 20\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.45200763])\n",
"new x0 = [0.45200763]\n",
"NEW Performance: {'x0': [array([0.45200763])], 'annotated': {'tp': 15, 'fp': 75, 'tn': 110, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 554, 'tn': 6965, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_label_similarity_mb_tuned\n",
"===== LF_comment_similarity_ma =========\n",
"x0 [array([0.50581573])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.50581573])], 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 5300\n",
"-0.009433962264150943\n",
"[0.50581573] -0.009433962264150943 15 {'x0': array([0.50581573]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"-0.007234843003906815\n",
"[0.37432669] -0.007234843003906815 15 {'x0': array([0.37432669]), 'annotated': {'tp': 15, 'fp': 178, 'tn': 7, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6911, 'tn': 608, 'fn': 0, 'coverage': 1.0}}\n",
"2.986095661846496\n",
"[0.60567331] 2.986095661846496 15 {'x0': array([0.60567331]), 'annotated': {'tp': 12, 'fp': 103, 'tn': 82, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3596, 'tn': 3923, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006770480704129994\n",
"[0.23134662] -0.006770480704129994 15 {'x0': array([0.23134662]), 'annotated': {'tp': 15, 'fp': 181, 'tn': 4, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7385, 'tn': 134, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006901311249137336\n",
"[0.30288362] -0.006901311249137336 15 {'x0': array([0.30288362]), 'annotated': {'tp': 15, 'fp': 180, 'tn': 5, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7245, 'tn': 274, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008369601606963508\n",
"[0.46269324] -0.008369601606963508 15 {'x0': array([0.46269324]), 'annotated': {'tp': 15, 'fp': 162, 'tn': 23, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5974, 'tn': 1545, 'fn': 0, 'coverage': 1.0}}\n",
"0.9902400936951006\n",
"[0.51730676] 0.9902400936951006 15 {'x0': array([0.51730676]), 'annotated': {'tp': 14, 'fp': 142, 'tn': 43, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5123, 'tn': 2396, 'fn': 0, 'coverage': 1.0}}\n",
"-0.007865345288658171\n",
"[0.42894022] -0.007865345288658171 15 {'x0': array([0.42894022]), 'annotated': {'tp': 15, 'fp': 168, 'tn': 17, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6357, 'tn': 1162, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00893016610108948\n",
"[0.48355375] -0.00893016610108948 15 {'x0': array([0.48355375]), 'annotated': {'tp': 15, 'fp': 153, 'tn': 32, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5599, 'tn': 1920, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009189487226612754\n",
"[0.49644625] -0.009189487226612754 15 {'x0': array([0.49644625]), 'annotated': {'tp': 15, 'fp': 152, 'tn': 33, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5441, 'tn': 2078, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009400263207369806\n",
"[0.50441426] -0.009400263207369806 15 {'x0': array([0.50441426]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5319, 'tn': 2200, 'fn': 0, 'coverage': 1.0}}\n",
"0.9904834411876665\n",
"[0.50933876] 0.9904834411876665 15 {'x0': array([0.50933876]), 'annotated': {'tp': 14, 'fp': 146, 'tn': 39, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5254, 'tn': 2265, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009304056568663937\n",
"[0.50137075] -0.009304056568663937 15 {'x0': array([0.50137075]), 'annotated': {'tp': 15, 'fp': 150, 'tn': 35, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5374, 'tn': 2145, 'fn': 0, 'coverage': 1.0}}\n",
"0.990551776266062\n",
"[0.50629525] 0.990551776266062 15 {'x0': array([0.50629525]), 'annotated': {'tp': 14, 'fp': 148, 'tn': 37, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5292, 'tn': 2227, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009373828271466067\n",
"[0.50325174] -0.009373828271466067 15 {'x0': array([0.50325174]), 'annotated': {'tp': 15, 'fp': 149, 'tn': 36, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5334, 'tn': 2185, 'fn': 0, 'coverage': 1.0}}\n",
"-0.00942684766214178\n",
"[0.50513273] -0.00942684766214178 15 {'x0': array([0.50513273]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5304, 'tn': 2215, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009432182607055273\n",
"[0.50557678] -0.009432182607055273 15 {'x0': array([0.50557678]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5301, 'tn': 2218, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009432182607055273\n",
"[0.50563424] -0.009432182607055273 15 {'x0': array([0.50563424]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5301, 'tn': 2218, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009432182607055273\n",
"[0.50566758] -0.009432182607055273 15 {'x0': array([0.50566758]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5301, 'tn': 2218, 'fn': 0, 'coverage': 1.0}}\n",
"0.9905660377358491\n",
"[0.50590733] 0.9905660377358491 15 {'x0': array([0.50590733]), 'annotated': {'tp': 14, 'fp': 148, 'tn': 37, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009433962264150943\n",
"[0.50575915] -0.009433962264150943 15 {'x0': array([0.50575915]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009433962264150943\n",
"[0.50581575] -0.009433962264150943 15 {'x0': array([0.50581575]), 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"0.9905660377358491\n",
"[0.50584908] 0.9905660377358491 15 {'x0': array([0.50584908]), 'annotated': {'tp': 14, 'fp': 148, 'tn': 37, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.601248025894165 s\n",
" direc: array([[1.]])\n",
" fun: -0.009433962264150943\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 23\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.50581575])\n",
"new x0 = [0.50581575]\n",
"NEW Performance: {'x0': [array([0.50581575])], 'annotated': {'tp': 15, 'fp': 148, 'tn': 37, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5300, 'tn': 2219, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_comment_similarity_ma_tuned\n",
"===== LF_comment_similarity_mb =========\n",
"x0 [array([0.14427887])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.14427887])], 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 5109\n",
"-0.009786651008025053\n",
"[0.14427887] -0.009786651008025053 15 {'x0': array([0.14427887]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"5.96299037749815\n",
"[0.37432669] 5.96299037749815 15 {'x0': array([0.37432669]), 'annotated': {'tp': 9, 'fp': 78, 'tn': 107, 'fn': 6, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 1351, 'tn': 6168, 'fn': 0, 'coverage': 1.0}}\n",
"12.206349206349206\n",
"[0.60567331] 12.206349206349206 15 {'x0': array([0.60567331]), 'annotated': {'tp': 2, 'fp': 6, 'tn': 179, 'fn': 13, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 63, 'tn': 7456, 'fn': 0, 'coverage': 1.0}}\n",
"1.9860763018657757\n",
"[0.23134662] 1.9860763018657757 15 {'x0': array([0.23134662]), 'annotated': {'tp': 13, 'fp': 157, 'tn': 28, 'fn': 2, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3591, 'tn': 3928, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.009718172983479106\n",
"[0.14298007] -0.009718172983479106 15 {'x0': array([0.14298007]), 'annotated': {'tp': 15, 'fp': 175, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5145, 'tn': 2374, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008322237017310254\n",
"[0.08836654] -0.008322237017310254 15 {'x0': array([0.08836654]), 'annotated': {'tp': 15, 'fp': 177, 'tn': 8, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6008, 'tn': 1511, 'fn': 0, 'coverage': 1.0}}\n",
"-0.008933357155619081\n",
"[0.11575412] -0.008933357155619081 15 {'x0': array([0.11575412]), 'annotated': {'tp': 15, 'fp': 176, 'tn': 9, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5597, 'tn': 1922, 'fn': 0, 'coverage': 1.0}}\n",
"0.9890302764370338\n",
"[0.17673309] 0.9890302764370338 15 {'x0': array([0.17673309]), 'annotated': {'tp': 14, 'fp': 173, 'tn': 12, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4558, 'tn': 2961, 'fn': 0, 'coverage': 1.0}}\n",
"0.989839463523674\n",
"[0.15587258] 0.989839463523674 15 {'x0': array([0.15587258]), 'annotated': {'tp': 14, 'fp': 174, 'tn': 11, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4921, 'tn': 2598, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009347541596560104\n",
"[0.13258069] -0.009347541596560104 15 {'x0': array([0.13258069]), 'annotated': {'tp': 15, 'fp': 175, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5349, 'tn': 2170, 'fn': 0, 'coverage': 1.0}}\n",
"0.9900911613158938\n",
"[0.14790457] 0.9900911613158938 15 {'x0': array([0.14790457]), 'annotated': {'tp': 14, 'fp': 174, 'tn': 11, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5046, 'tn': 2473, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009589566551591868\n",
"[0.13900786] -0.009589566551591868 15 {'x0': array([0.13900786]), 'annotated': {'tp': 15, 'fp': 175, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5214, 'tn': 2305, 'fn': 0, 'coverage': 1.0}}\n",
"0.9902095163501077\n",
"[0.14486106] 0.9902095163501077 15 {'x0': array([0.14486106]), 'annotated': {'tp': 14, 'fp': 174, 'tn': 11, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5107, 'tn': 2412, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009667440061871617\n",
"[0.14146282] -0.009667440061871617 15 {'x0': array([0.14146282]), 'annotated': {'tp': 15, 'fp': 175, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5172, 'tn': 2347, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009759906304899472\n",
"[0.14369855] -0.009759906304899472 15 {'x0': array([0.14369855]), 'annotated': {'tp': 15, 'fp': 175, 'tn': 10, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5123, 'tn': 2396, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009778994719342852\n",
"[0.14414259] -0.009778994719342852 15 {'x0': array([0.14414259]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5113, 'tn': 2406, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009786651008025053\n",
"[0.14441702] -0.009786651008025053 15 {'x0': array([0.14441702]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"0.990213348991975\n",
"[0.14458663] 0.990213348991975 15 {'x0': array([0.14458663]), 'annotated': {'tp': 14, 'fp': 174, 'tn': 11, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009786651008025053\n",
"[0.1443122] -0.009786651008025053 15 {'x0': array([0.1443122]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009786651008025053\n",
"[0.14427887] -0.009786651008025053 15 {'x0': array([0.14427887]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"-0.009782821365681862\n",
"[0.14422681] -0.009782821365681862 15 {'x0': array([0.14422681]), 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5111, 'tn': 2408, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.4310598373413086 s\n",
" direc: array([[1.]])\n",
" fun: -0.009786651008025053\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 21\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.14427887])\n",
"new x0 = [0.14427887]\n",
"NEW Performance: {'x0': [array([0.14427887])], 'annotated': {'tp': 15, 'fp': 174, 'tn': 11, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5109, 'tn': 2410, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_comment_similarity_mb_tuned\n",
"===== LF_random_forest_prob =========\n",
"x0 [array([0.08366009])]\n",
"bounds [(0, array([0.35437816]))]\n",
"OLD Performance: {'x0': [array([0.08366009])], 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 2\n",
"-25.0\n",
"[0.08366009] -25.0 15 {'x0': array([0.08366009]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.13536041] -25.0 15 {'x0': array([0.13536041]), 'annotated': {'tp': 15, 'fp': 3, 'tn': 182, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"0\n",
"[0.21901775] 0 15 {'x0': array([0.21901775]), 'annotated': {'tp': 15, 'fp': 2, 'tn': 183, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7519, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08365734] -25.0 15 {'x0': array([0.08365734]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.10950887] -25.0 15 {'x0': array([0.10950887]), 'annotated': {'tp': 15, 'fp': 3, 'tn': 182, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.09963446] -25.0 15 {'x0': array([0.09963446]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.09353174] -25.0 15 {'x0': array([0.09353174]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08976006] -25.0 15 {'x0': array([0.08976006]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08742902] -25.0 15 {'x0': array([0.08742902]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08598837] -25.0 15 {'x0': array([0.08598837]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08509799] -25.0 15 {'x0': array([0.08509799]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08454771] -25.0 15 {'x0': array([0.08454771]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08420762] -25.0 15 {'x0': array([0.08420762]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08399743] -25.0 15 {'x0': array([0.08399743]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08386752] -25.0 15 {'x0': array([0.08386752]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08378724] -25.0 15 {'x0': array([0.08378724]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08373762] -25.0 15 {'x0': array([0.08373762]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-25.0\n",
"[0.08370429] -25.0 15 {'x0': array([0.08370429]), 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.2357239723205566 s\n",
" direc: array([[1.]])\n",
" fun: -25.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 18\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.08370429])\n",
"new x0 = [0.08370429]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"NEW Performance: {'x0': [array([0.08370429])], 'annotated': {'tp': 15, 'fp': 4, 'tn': 181, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_random_forest_prob_tuned\n",
"===== LF_logistic_regression_prob =========\n",
"x0 [array([0.1166723])]\n",
"bounds [(0, array([0.15272603]))]\n",
"OLD Performance: {'x0': [array([0.1166723])], 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 2\n",
"-22.0\n",
"[0.1166723] -22.0 15 {'x0': array([0.1166723]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-2.5555555555555554\n",
"[0.05833615] -2.5555555555555554 15 {'x0': array([0.05833615]), 'annotated': {'tp': 12, 'fp': 10, 'tn': 175, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 9, 'tn': 7510, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09438988] -22.0 15 {'x0': array([0.09438988]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.11667231] -22.0 15 {'x0': array([0.11667231]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.10553109] -22.0 15 {'x0': array([0.10553109]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.10127553] -22.0 15 {'x0': array([0.10127553]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09864544] -22.0 15 {'x0': array([0.09864544]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09701996] -22.0 15 {'x0': array([0.09701996]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09601536] -22.0 15 {'x0': array([0.09601536]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09539448] -22.0 15 {'x0': array([0.09539448]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09501076] -22.0 15 {'x0': array([0.09501076]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.0947736] -22.0 15 {'x0': array([0.0947736]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09462703] -22.0 15 {'x0': array([0.09462703]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09453645] -22.0 15 {'x0': array([0.09453645]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09448046] -22.0 15 {'x0': array([0.09448046]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-22.0\n",
"[0.09444586] -22.0 15 {'x0': array([0.09444586]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 1.082435131072998 s\n",
" direc: array([[1.]])\n",
" fun: -22.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 16\n",
" nit: 1\n",
" status: 0\n",
" success: True\n",
" x: array([0.09444586])\n",
"new x0 = [0.09444586]\n",
"NEW Performance: {'x0': [array([0.09444586])], 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_logistic_regression_prob_tuned\n",
"===== LF_xgboost_prob =========\n",
"x0 [array([0.23139809])]\n",
"bounds [(0, 0.98)]\n",
"OLD Performance: {'x0': [array([0.23139809])], 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7519, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 0\n",
"updated boundary [(0, array([0.21139809]))]\n",
"1\n",
"[0.21139809] 1 15 {'x0': array([0.21139809]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7519, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.1306512] -24.0 15 {'x0': array([0.1306512]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"1\n",
"[0.16149377] 1 15 {'x0': array([0.16149377]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 0, 'tn': 7519, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.10569904] -24.0 15 {'x0': array([0.10569904]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.09616817] -24.0 15 {'x0': array([0.09616817]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.09027776] -24.0 15 {'x0': array([0.09027776]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08663729] -24.0 15 {'x0': array([0.08663729]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08438736] -24.0 15 {'x0': array([0.08438736]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08299682] -24.0 15 {'x0': array([0.08299682]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08213742] -24.0 15 {'x0': array([0.08213742]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08160628] -24.0 15 {'x0': array([0.08160628]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08127802] -24.0 15 {'x0': array([0.08127802]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08107515] -24.0 15 {'x0': array([0.08107515]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08094976] -24.0 15 {'x0': array([0.08094976]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08087227] -24.0 15 {'x0': array([0.08087227]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08082438] -24.0 15 {'x0': array([0.08082438]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08079104] -24.0 15 {'x0': array([0.08079104]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-0.006649820454847719\n",
"[-0.04981601] -0.006649820454847719 15 {'x0': array([-0.04981601]), 'annotated': {'tp': 15, 'fp': 185, 'tn': 0, 'fn': 0, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 7519, 'tn': 0, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.1306512] -24.0 15 {'x0': array([0.1306512]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.04990432] -24.0 15 {'x0': array([0.04990432]), 'annotated': {'tp': 14, 'fp': 4, 'tn': 181, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-15.666666666666668\n",
"[0.03084257] -15.666666666666668 15 {'x0': array([0.03084257]), 'annotated': {'tp': 14, 'fp': 8, 'tn': 177, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.06168513] -24.0 15 {'x0': array([0.06168513]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.06896607] -24.0 15 {'x0': array([0.06896607]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07346594] -24.0 15 {'x0': array([0.07346594]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07624701] -24.0 15 {'x0': array([0.07624701]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07796581] -24.0 15 {'x0': array([0.07796581]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07902809] -24.0 15 {'x0': array([0.07902809]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07968461] -24.0 15 {'x0': array([0.07968461]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08009036] -24.0 15 {'x0': array([0.08009036]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08034113] -24.0 15 {'x0': array([0.08034113]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08049611] -24.0 15 {'x0': array([0.08049611]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0805919] -24.0 15 {'x0': array([0.0805919]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0806511] -24.0 15 {'x0': array([0.0806511]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08068769] -24.0 15 {'x0': array([0.08068769]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0807103] -24.0 15 {'x0': array([0.0807103]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08072427] -24.0 15 {'x0': array([0.08072427]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08073291] -24.0 15 {'x0': array([0.08073291]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08073825] -24.0 15 {'x0': array([0.08073825]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.1306512] -24.0 15 {'x0': array([0.1306512]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.04990432] -24.0 15 {'x0': array([0.04990432]), 'annotated': {'tp': 14, 'fp': 4, 'tn': 181, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-15.666666666666668\n",
"[0.03084257] -15.666666666666668 15 {'x0': array([0.03084257]), 'annotated': {'tp': 14, 'fp': 8, 'tn': 177, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.06168513] -24.0 15 {'x0': array([0.06168513]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.06896607] -24.0 15 {'x0': array([0.06896607]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07346594] -24.0 15 {'x0': array([0.07346594]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07624701] -24.0 15 {'x0': array([0.07624701]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07796581] -24.0 15 {'x0': array([0.07796581]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07902809] -24.0 15 {'x0': array([0.07902809]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.07968461] -24.0 15 {'x0': array([0.07968461]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08009036] -24.0 15 {'x0': array([0.08009036]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08034113] -24.0 15 {'x0': array([0.08034113]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08049611] -24.0 15 {'x0': array([0.08049611]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0805919] -24.0 15 {'x0': array([0.0805919]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0806511] -24.0 15 {'x0': array([0.0806511]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08068769] -24.0 15 {'x0': array([0.08068769]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0807103] -24.0 15 {'x0': array([0.0807103]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08072427] -24.0 15 {'x0': array([0.08072427]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08073291] -24.0 15 {'x0': array([0.08073291]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08073825] -24.0 15 {'x0': array([0.08073825]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074155] -24.0 15 {'x0': array([0.08074155]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074359] -24.0 15 {'x0': array([0.08074359]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074485] -24.0 15 {'x0': array([0.08074485]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-24.0\n",
"[0.08074562] -24.0 15 {'x0': array([0.08074562]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074611] -24.0 15 {'x0': array([0.08074611]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0807464] -24.0 15 {'x0': array([0.0807464]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074659] -24.0 15 {'x0': array([0.08074659]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.0807467] -24.0 15 {'x0': array([0.0807467]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074677] -24.0 15 {'x0': array([0.08074677]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074681] -24.0 15 {'x0': array([0.08074681]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074684] -24.0 15 {'x0': array([0.08074684]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074686] -24.0 15 {'x0': array([0.08074686]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074687] -24.0 15 {'x0': array([0.08074687]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074687] -24.0 15 {'x0': array([0.08074687]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"-24.0\n",
"[0.08074688] -24.0 15 {'x0': array([0.08074688]), 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 5.255204200744629 s\n",
" direc: array([[-5.27936097e-05]])\n",
" fun: -24.0\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 78\n",
" nit: 2\n",
" status: 0\n",
" success: True\n",
" x: array([0.08074688])\n",
"new x0 = [0.08074688]\n",
"NEW Performance: {'x0': [array([0.08074688])], 'annotated': {'tp': 14, 'fp': 3, 'tn': 182, 'fn': 1, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 2, 'tn': 7517, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_xgboost_prob_tuned\n",
"===== LF_mlp_prob =========\n",
"x0 [array([0.0510234])]\n",
"bounds [(0, array([0.06390907]))]\n",
"OLD Performance: {'x0': [array([0.0510234])], 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4, 'tn': 7515, 'fn': 0, 'coverage': 1.0}}\n",
"num_predicted_matches = 4\n",
"-9.5\n",
"[0.0510234] -9.5 15 {'x0': array([0.0510234]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 4, 'tn': 7515, 'fn': 0, 'coverage': 1.0}}\n",
"0.22222222222222232\n",
"[0.02441109] 0.22222222222222232 15 {'x0': array([0.02441109]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 18, 'tn': 7501, 'fn': 0, 'coverage': 1.0}}\n",
"-5.333333333333334\n",
"[0.03949798] -5.333333333333334 15 {'x0': array([0.03949798]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6, 'tn': 7513, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.04882218] -7.0 15 {'x0': array([0.04882218]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7514, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567352] -13.666666666666668 15 {'x0': array([0.05567352]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881922] -13.666666666666668 15 {'x0': array([0.05881922]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05724637] -13.666666666666668 15 {'x0': array([0.05724637]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05664559] -13.666666666666668 15 {'x0': array([0.05664559]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05627429] -13.666666666666668 15 {'x0': array([0.05627429]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05604482] -13.666666666666668 15 {'x0': array([0.05604482]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05590299] -13.666666666666668 15 {'x0': array([0.05590299]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05581534] -13.666666666666668 15 {'x0': array([0.05581534]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05576117] -13.666666666666668 15 {'x0': array([0.05576117]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05572769] -13.666666666666668 15 {'x0': array([0.05572769]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.06043197] -13.666666666666668 15 {'x0': array([0.06043197]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"0.22222222222222232\n",
"[0.02441109] 0.22222222222222232 15 {'x0': array([0.02441109]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 18, 'tn': 7501, 'fn': 0, 'coverage': 1.0}}\n",
"-5.333333333333334\n",
"[0.03949798] -5.333333333333334 15 {'x0': array([0.03949798]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6, 'tn': 7513, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.04882218] -7.0 15 {'x0': array([0.04882218]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7514, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567352] -13.666666666666668 15 {'x0': array([0.05567352]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881922] -13.666666666666668 15 {'x0': array([0.05881922]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05724637] -13.666666666666668 15 {'x0': array([0.05724637]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05664559] -13.666666666666668 15 {'x0': array([0.05664559]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05627429] -13.666666666666668 15 {'x0': array([0.05627429]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05604482] -13.666666666666668 15 {'x0': array([0.05604482]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-13.666666666666668\n",
"[0.05590299] -13.666666666666668 15 {'x0': array([0.05590299]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05581534] -13.666666666666668 15 {'x0': array([0.05581534]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05576117] -13.666666666666668 15 {'x0': array([0.05576117]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05572769] -13.666666666666668 15 {'x0': array([0.05572769]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.055707] -13.666666666666668 15 {'x0': array([0.055707]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05569421] -13.666666666666668 15 {'x0': array([0.05569421]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.0556863] -13.666666666666668 15 {'x0': array([0.0556863]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05568142] -13.666666666666668 15 {'x0': array([0.05568142]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.0556784] -13.666666666666668 15 {'x0': array([0.0556784]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567653] -13.666666666666668 15 {'x0': array([0.05567653]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567538] -13.666666666666668 15 {'x0': array([0.05567538]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567467] -13.666666666666668 15 {'x0': array([0.05567467]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567423] -13.666666666666668 15 {'x0': array([0.05567423]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567396] -13.666666666666668 15 {'x0': array([0.05567396]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567379] -13.666666666666668 15 {'x0': array([0.05567379]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-5.333333333333334\n",
"[0.03949798] -5.333333333333334 15 {'x0': array([0.03949798]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 6, 'tn': 7513, 'fn': 0, 'coverage': 1.0}}\n",
"0.22222222222222232\n",
"[0.02441109] 0.22222222222222232 15 {'x0': array([0.02441109]), 'annotated': {'tp': 12, 'fp': 7, 'tn': 178, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 18, 'tn': 7501, 'fn': 0, 'coverage': 1.0}}\n",
"-7.0\n",
"[0.04882218] -7.0 15 {'x0': array([0.04882218]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 5, 'tn': 7514, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05567352] -13.666666666666668 15 {'x0': array([0.05567352]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881922] -13.666666666666668 15 {'x0': array([0.05881922]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05724637] -13.666666666666668 15 {'x0': array([0.05724637]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05784714] -13.666666666666668 15 {'x0': array([0.05784714]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05821844] -13.666666666666668 15 {'x0': array([0.05821844]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05844792] -13.666666666666668 15 {'x0': array([0.05844792]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05858974] -13.666666666666668 15 {'x0': array([0.05858974]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05867739] -13.666666666666668 15 {'x0': array([0.05867739]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05873157] -13.666666666666668 15 {'x0': array([0.05873157]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05876505] -13.666666666666668 15 {'x0': array([0.05876505]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05878574] -13.666666666666668 15 {'x0': array([0.05878574]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05879853] -13.666666666666668 15 {'x0': array([0.05879853]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05880643] -13.666666666666668 15 {'x0': array([0.05880643]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881131] -13.666666666666668 15 {'x0': array([0.05881131]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881433] -13.666666666666668 15 {'x0': array([0.05881433]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.0588162] -13.666666666666668 15 {'x0': array([0.0588162]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881735] -13.666666666666668 15 {'x0': array([0.05881735]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881806] -13.666666666666668 15 {'x0': array([0.05881806]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.0588185] -13.666666666666668 15 {'x0': array([0.0588185]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881878] -13.666666666666668 15 {'x0': array([0.05881878]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881894] -13.666666666666668 15 {'x0': array([0.05881894]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881905] -13.666666666666668 15 {'x0': array([0.05881905]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-13.666666666666668\n",
"[0.05881911] -13.666666666666668 15 {'x0': array([0.05881911]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881915] -13.666666666666668 15 {'x0': array([0.05881915]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881918] -13.666666666666668 15 {'x0': array([0.05881918]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881919] -13.666666666666668 15 {'x0': array([0.05881919]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.0588192] -13.666666666666668 15 {'x0': array([0.0588192]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881921] -13.666666666666668 15 {'x0': array([0.05881921]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881921] -13.666666666666668 15 {'x0': array([0.05881921]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"-13.666666666666668\n",
"[0.05881921] -13.666666666666668 15 {'x0': array([0.05881921]), 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"Optimizing Time: 4.909954071044922 s\n",
" direc: array([[-5.38996778e-05]])\n",
" fun: -13.666666666666668\n",
" message: 'Optimization terminated successfully.'\n",
" nfev: 72\n",
" nit: 2\n",
" status: 0\n",
" success: True\n",
" x: array([0.05881921])\n",
"new x0 = [0.05881921]\n",
"NEW Performance: {'x0': [array([0.05881921])], 'annotated': {'tp': 12, 'fp': 6, 'tn': 179, 'fn': 3, 'coverage': 1.0}, 'predicted': {'tp': 0, 'fp': 3, 'tn': 7516, 'fn': 0, 'coverage': 1.0}}\n",
"\n",
"\n",
"LF_mlp_prob_tuned\n",
"LF augumentation time: 24.296222925186157 s\n",
"[0.5923076923076923, 0.5923076923076923, 0.1, 0.20588235294117646, 0.5727272727272728, 0.5923076923076923, 0.5923076923076923, 0.0448, 0.0448, 0.1, 0.1, 0.1, 0.5499999999999999, 0.5384615384615384, 0.1, 0.42, 0.39999999999999997, 0.04686192468619246, 0.06956521739130433, 0.07943262411347517, 0.5, 0.05258215962441314, 0.6, 0.07999999999999999, 0.5157894736842105, 0.7, 0.07225806451612903, 0.5923076923076923, 0.5923076923076923]\n",
"Done with DualLoop\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f8ba525b0efc4569879030412453ce07",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/250 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Done with WeSAL\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f7bec89d78354250967c65f857e37a12",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/250 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Done with AL-RF\n"
]
}
],
"source": [
"dataset_name = 'ai4eu-2'\n",
"case_name = 'various_lfs'\n",
"methods = [\n",
" 'DualLoop', \n",
" 'WeSAL', \n",
" 'AL-RF', \n",
"# 'DualLoop_without_tuning',\n",
"# 'DualLoop_without_slow_loop',\n",
"# 'DualLoop_with_entropy',\n",
"# 'DualLoop_with_normal_ensemble'\n",
"]\n",
"\n",
"results = {}\n",
"\n",
"for method in methods:\n",
" result = run_experiment(cfg, dataset_name, method, case_name)\n",
" results[method] = result\n",
" print(\"Done with \" + method)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "22a3ccd2",
"metadata": {},
"outputs": [],
"source": [
"methods = [\n",
" 'WeSAL', \n",
" 'AL-RF', \n",
" 'DualLoop',\n",
"# 'DualLoop_without_slow_loop',\n",
"# 'DualLoop_with_entropy',\n",
"# 'DualLoop_with_normal_ensemble'\n",
"]\n",
"\n",
"measurements = []\n",
"for method in methods:\n",
" result = results[method]\n",
" for iteration in result:\n",
" r = result[iteration]\n",
" f1 = r['f1'] * 100.0\n",
" measurement = {\n",
" 'methods': method,\n",
" 'iteration': iteration,\n",
" 'metric': f1\n",
" } \n",
" measurements.append(measurement)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "b3627dac",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_f1_result(measurements, dataset_name)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ade1836e",
"metadata": {},
"outputs": [],
"source": [
"plot_f1_result(measurements, dataset_name)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2e802c60",
"metadata": {},
"outputs": [],
"source": [
"plot_f1_result(measurements, dataset_name)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1a36e298",
"metadata": {},
"outputs": [],
"source": [
"results['DualLoop']"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0938094",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}