{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Multiple disease prediction system - Parkinsons.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyPgH5xu9ZLOpcMFNkcpInRX"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","metadata":{"id":"9B5Zl1UOBMAJ"},"source":["Importing the Dependencies"]},{"cell_type":"code","metadata":{"id":"YOCpZ1Vm6cfW","executionInfo":{"status":"ok","timestamp":1653200307851,"user_tz":-330,"elapsed":2162,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["import numpy as np\n","import pandas as pd\n","from sklearn.model_selection import train_test_split\n","from sklearn import svm\n","from sklearn.metrics import accuracy_score"],"execution_count":1,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"PZm-USrtB_q4"},"source":["Data Collection & Analysis"]},{"cell_type":"code","metadata":{"id":"5YC2lGuVBiZA","executionInfo":{"status":"ok","timestamp":1653200307854,"user_tz":-330,"elapsed":23,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["# loading the data from csv file to a Pandas DataFrame\n","parkinsons_data = pd.read_csv('/content/parkinsons.csv')"],"execution_count":2,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":299},"id":"Iw8z6w60Djd2","executionInfo":{"status":"ok","timestamp":1653200307855,"user_tz":-330,"elapsed":23,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"ca177b83-79f9-46c5-89c0-42985b1923ba"},"source":["# printing the first 5 rows of the dataframe\n","parkinsons_data.head()"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":[" name MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) \\\n","0 phon_R01_S01_1 119.992 157.302 74.997 0.00784 \n","1 phon_R01_S01_2 122.400 148.650 113.819 0.00968 \n","2 phon_R01_S01_3 116.682 131.111 111.555 0.01050 \n","3 phon_R01_S01_4 116.676 137.871 111.366 0.00997 \n","4 phon_R01_S01_5 116.014 141.781 110.655 0.01284 \n","\n"," MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer ... \\\n","0 0.00007 0.00370 0.00554 0.01109 0.04374 ... \n","1 0.00008 0.00465 0.00696 0.01394 0.06134 ... \n","2 0.00009 0.00544 0.00781 0.01633 0.05233 ... \n","3 0.00009 0.00502 0.00698 0.01505 0.05492 ... \n","4 0.00011 0.00655 0.00908 0.01966 0.06425 ... \n","\n"," Shimmer:DDA NHR HNR status RPDE DFA spread1 \\\n","0 0.06545 0.02211 21.033 1 0.414783 0.815285 -4.813031 \n","1 0.09403 0.01929 19.085 1 0.458359 0.819521 -4.075192 \n","2 0.08270 0.01309 20.651 1 0.429895 0.825288 -4.443179 \n","3 0.08771 0.01353 20.644 1 0.434969 0.819235 -4.117501 \n","4 0.10470 0.01767 19.649 1 0.417356 0.823484 -3.747787 \n","\n"," spread2 D2 PPE \n","0 0.266482 2.301442 0.284654 \n","1 0.335590 2.486855 0.368674 \n","2 0.311173 2.342259 0.332634 \n","3 0.334147 2.405554 0.368975 \n","4 0.234513 2.332180 0.410335 \n","\n","[5 rows x 24 columns]"],"text/html":["\n"," <div id=\"df-09ab8692-d189-4aac-8b73-032a2a0c64be\">\n"," <div class=\"colab-df-container\">\n"," <div>\n","<style scoped>\n"," .dataframe tbody tr th:only-of-type {\n"," vertical-align: middle;\n"," }\n","\n"," .dataframe tbody tr th {\n"," vertical-align: top;\n"," }\n","\n"," .dataframe thead th {\n"," text-align: right;\n"," }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n"," <thead>\n"," <tr style=\"text-align: right;\">\n"," <th></th>\n"," <th>name</th>\n"," <th>MDVP:Fo(Hz)</th>\n"," <th>MDVP:Fhi(Hz)</th>\n"," <th>MDVP:Flo(Hz)</th>\n"," <th>MDVP:Jitter(%)</th>\n"," <th>MDVP:Jitter(Abs)</th>\n"," <th>MDVP:RAP</th>\n"," <th>MDVP:PPQ</th>\n"," <th>Jitter:DDP</th>\n"," <th>MDVP:Shimmer</th>\n"," <th>...</th>\n"," <th>Shimmer:DDA</th>\n"," <th>NHR</th>\n"," <th>HNR</th>\n"," <th>status</th>\n"," <th>RPDE</th>\n"," <th>DFA</th>\n"," <th>spread1</th>\n"," <th>spread2</th>\n"," <th>D2</th>\n"," <th>PPE</th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>0</th>\n"," <td>phon_R01_S01_1</td>\n"," <td>119.992</td>\n"," <td>157.302</td>\n"," <td>74.997</td>\n"," <td>0.00784</td>\n"," <td>0.00007</td>\n"," <td>0.00370</td>\n"," <td>0.00554</td>\n"," <td>0.01109</td>\n"," <td>0.04374</td>\n"," <td>...</td>\n"," <td>0.06545</td>\n"," <td>0.02211</td>\n"," <td>21.033</td>\n"," <td>1</td>\n"," <td>0.414783</td>\n"," <td>0.815285</td>\n"," <td>-4.813031</td>\n"," <td>0.266482</td>\n"," <td>2.301442</td>\n"," <td>0.284654</td>\n"," </tr>\n"," <tr>\n"," <th>1</th>\n"," <td>phon_R01_S01_2</td>\n"," <td>122.400</td>\n"," <td>148.650</td>\n"," <td>113.819</td>\n"," <td>0.00968</td>\n"," <td>0.00008</td>\n"," <td>0.00465</td>\n"," <td>0.00696</td>\n"," <td>0.01394</td>\n"," <td>0.06134</td>\n"," <td>...</td>\n"," <td>0.09403</td>\n"," <td>0.01929</td>\n"," <td>19.085</td>\n"," <td>1</td>\n"," <td>0.458359</td>\n"," <td>0.819521</td>\n"," <td>-4.075192</td>\n"," <td>0.335590</td>\n"," <td>2.486855</td>\n"," <td>0.368674</td>\n"," </tr>\n"," <tr>\n"," <th>2</th>\n"," <td>phon_R01_S01_3</td>\n"," <td>116.682</td>\n"," <td>131.111</td>\n"," <td>111.555</td>\n"," <td>0.01050</td>\n"," <td>0.00009</td>\n"," <td>0.00544</td>\n"," <td>0.00781</td>\n"," <td>0.01633</td>\n"," <td>0.05233</td>\n"," <td>...</td>\n"," <td>0.08270</td>\n"," <td>0.01309</td>\n"," <td>20.651</td>\n"," <td>1</td>\n"," <td>0.429895</td>\n"," <td>0.825288</td>\n"," <td>-4.443179</td>\n"," <td>0.311173</td>\n"," <td>2.342259</td>\n"," <td>0.332634</td>\n"," </tr>\n"," <tr>\n"," <th>3</th>\n"," <td>phon_R01_S01_4</td>\n"," <td>116.676</td>\n"," <td>137.871</td>\n"," <td>111.366</td>\n"," <td>0.00997</td>\n"," <td>0.00009</td>\n"," <td>0.00502</td>\n"," <td>0.00698</td>\n"," <td>0.01505</td>\n"," <td>0.05492</td>\n"," <td>...</td>\n"," <td>0.08771</td>\n"," <td>0.01353</td>\n"," <td>20.644</td>\n"," <td>1</td>\n"," <td>0.434969</td>\n"," <td>0.819235</td>\n"," <td>-4.117501</td>\n"," <td>0.334147</td>\n"," <td>2.405554</td>\n"," <td>0.368975</td>\n"," </tr>\n"," <tr>\n"," <th>4</th>\n"," <td>phon_R01_S01_5</td>\n"," <td>116.014</td>\n"," <td>141.781</td>\n"," <td>110.655</td>\n"," <td>0.01284</td>\n"," <td>0.00011</td>\n"," <td>0.00655</td>\n"," <td>0.00908</td>\n"," <td>0.01966</td>\n"," <td>0.06425</td>\n"," <td>...</td>\n"," <td>0.10470</td>\n"," <td>0.01767</td>\n"," <td>19.649</td>\n"," <td>1</td>\n"," <td>0.417356</td>\n"," <td>0.823484</td>\n"," <td>-3.747787</td>\n"," <td>0.234513</td>\n"," <td>2.332180</td>\n"," <td>0.410335</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>5 rows × 24 columns</p>\n","</div>\n"," <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-09ab8692-d189-4aac-8b73-032a2a0c64be')\"\n"," title=\"Convert this dataframe to an interactive table.\"\n"," style=\"display:none;\">\n"," \n"," <svg xmlns=\"http://www.w3.org/2000/svg\" 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'block' : 'none';\n","\n"," async function convertToInteractive(key) {\n"," const element = document.querySelector('#df-09ab8692-d189-4aac-8b73-032a2a0c64be');\n"," const dataTable =\n"," await google.colab.kernel.invokeFunction('convertToInteractive',\n"," [key], {});\n"," if (!dataTable) return;\n","\n"," const docLinkHtml = 'Like what you see? Visit the ' +\n"," '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n"," + ' to learn more about interactive tables.';\n"," element.innerHTML = '';\n"," dataTable['output_type'] = 'display_data';\n"," await google.colab.output.renderOutput(dataTable, element);\n"," const docLink = document.createElement('div');\n"," docLink.innerHTML = docLinkHtml;\n"," element.appendChild(docLink);\n"," }\n"," </script>\n"," </div>\n"," </div>\n"," "]},"metadata":{},"execution_count":3}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cK7L_o2TDuZb","executionInfo":{"status":"ok","timestamp":1653200307855,"user_tz":-330,"elapsed":19,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"ff4ba57f-ef7c-42e3-e76d-c6cd69e8b250"},"source":["# number of rows and columns in the dataframe\n","parkinsons_data.shape"],"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(195, 24)"]},"metadata":{},"execution_count":4}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NLmzHIgnEGi4","executionInfo":{"status":"ok","timestamp":1653200307856,"user_tz":-330,"elapsed":17,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"59986869-f8e1-47a7-cd80-aa699514e488"},"source":["# getting more information about the dataset\n","parkinsons_data.info()"],"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 195 entries, 0 to 194\n","Data columns (total 24 columns):\n"," # Column Non-Null Count Dtype \n","--- ------ -------------- ----- \n"," 0 name 195 non-null object \n"," 1 MDVP:Fo(Hz) 195 non-null float64\n"," 2 MDVP:Fhi(Hz) 195 non-null float64\n"," 3 MDVP:Flo(Hz) 195 non-null float64\n"," 4 MDVP:Jitter(%) 195 non-null float64\n"," 5 MDVP:Jitter(Abs) 195 non-null float64\n"," 6 MDVP:RAP 195 non-null float64\n"," 7 MDVP:PPQ 195 non-null float64\n"," 8 Jitter:DDP 195 non-null float64\n"," 9 MDVP:Shimmer 195 non-null float64\n"," 10 MDVP:Shimmer(dB) 195 non-null float64\n"," 11 Shimmer:APQ3 195 non-null float64\n"," 12 Shimmer:APQ5 195 non-null float64\n"," 13 MDVP:APQ 195 non-null float64\n"," 14 Shimmer:DDA 195 non-null float64\n"," 15 NHR 195 non-null float64\n"," 16 HNR 195 non-null float64\n"," 17 status 195 non-null int64 \n"," 18 RPDE 195 non-null float64\n"," 19 DFA 195 non-null float64\n"," 20 spread1 195 non-null float64\n"," 21 spread2 195 non-null float64\n"," 22 D2 195 non-null float64\n"," 23 PPE 195 non-null float64\n","dtypes: float64(22), int64(1), object(1)\n","memory usage: 36.7+ KB\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"70rgu_k4ET9F","executionInfo":{"status":"ok","timestamp":1653200307857,"user_tz":-330,"elapsed":15,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"9d86783c-8f01-468a-a9a0-04552ebc10c7"},"source":["# checking for missing values in each column\n","parkinsons_data.isnull().sum()"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["name 0\n","MDVP:Fo(Hz) 0\n","MDVP:Fhi(Hz) 0\n","MDVP:Flo(Hz) 0\n","MDVP:Jitter(%) 0\n","MDVP:Jitter(Abs) 0\n","MDVP:RAP 0\n","MDVP:PPQ 0\n","Jitter:DDP 0\n","MDVP:Shimmer 0\n","MDVP:Shimmer(dB) 0\n","Shimmer:APQ3 0\n","Shimmer:APQ5 0\n","MDVP:APQ 0\n","Shimmer:DDA 0\n","NHR 0\n","HNR 0\n","status 0\n","RPDE 0\n","DFA 0\n","spread1 0\n","spread2 0\n","D2 0\n","PPE 0\n","dtype: int64"]},"metadata":{},"execution_count":6}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":394},"id":"1AxFu0-nEhSA","executionInfo":{"status":"ok","timestamp":1653200308700,"user_tz":-330,"elapsed":853,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"333d5e58-f085-43dc-ccb1-e7fc75084bcf"},"source":["# getting some statistical measures about the data\n","parkinsons_data.describe()"],"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":[" MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) \\\n","count 195.000000 195.000000 195.000000 195.000000 \n","mean 154.228641 197.104918 116.324631 0.006220 \n","std 41.390065 91.491548 43.521413 0.004848 \n","min 88.333000 102.145000 65.476000 0.001680 \n","25% 117.572000 134.862500 84.291000 0.003460 \n","50% 148.790000 175.829000 104.315000 0.004940 \n","75% 182.769000 224.205500 140.018500 0.007365 \n","max 260.105000 592.030000 239.170000 0.033160 \n","\n"," MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer \\\n","count 195.000000 195.000000 195.000000 195.000000 195.000000 \n","mean 0.000044 0.003306 0.003446 0.009920 0.029709 \n","std 0.000035 0.002968 0.002759 0.008903 0.018857 \n","min 0.000007 0.000680 0.000920 0.002040 0.009540 \n","25% 0.000020 0.001660 0.001860 0.004985 0.016505 \n","50% 0.000030 0.002500 0.002690 0.007490 0.022970 \n","75% 0.000060 0.003835 0.003955 0.011505 0.037885 \n","max 0.000260 0.021440 0.019580 0.064330 0.119080 \n","\n"," MDVP:Shimmer(dB) ... Shimmer:DDA NHR HNR status \\\n","count 195.000000 ... 195.000000 195.000000 195.000000 195.000000 \n","mean 0.282251 ... 0.046993 0.024847 21.885974 0.753846 \n","std 0.194877 ... 0.030459 0.040418 4.425764 0.431878 \n","min 0.085000 ... 0.013640 0.000650 8.441000 0.000000 \n","25% 0.148500 ... 0.024735 0.005925 19.198000 1.000000 \n","50% 0.221000 ... 0.038360 0.011660 22.085000 1.000000 \n","75% 0.350000 ... 0.060795 0.025640 25.075500 1.000000 \n","max 1.302000 ... 0.169420 0.314820 33.047000 1.000000 \n","\n"," RPDE DFA spread1 spread2 D2 PPE \n","count 195.000000 195.000000 195.000000 195.000000 195.000000 195.000000 \n","mean 0.498536 0.718099 -5.684397 0.226510 2.381826 0.206552 \n","std 0.103942 0.055336 1.090208 0.083406 0.382799 0.090119 \n","min 0.256570 0.574282 -7.964984 0.006274 1.423287 0.044539 \n","25% 0.421306 0.674758 -6.450096 0.174351 2.099125 0.137451 \n","50% 0.495954 0.722254 -5.720868 0.218885 2.361532 0.194052 \n","75% 0.587562 0.761881 -5.046192 0.279234 2.636456 0.252980 \n","max 0.685151 0.825288 -2.434031 0.450493 3.671155 0.527367 \n","\n","[8 rows x 23 columns]"],"text/html":["\n"," <div id=\"df-b83bb5a5-5785-498f-b146-d62b868ce2a6\">\n"," <div class=\"colab-df-container\">\n"," <div>\n","<style scoped>\n"," .dataframe tbody tr th:only-of-type {\n"," vertical-align: middle;\n"," }\n","\n"," .dataframe tbody tr th {\n"," vertical-align: top;\n"," }\n","\n"," .dataframe thead th {\n"," text-align: right;\n"," }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n"," <thead>\n"," <tr style=\"text-align: right;\">\n"," <th></th>\n"," <th>MDVP:Fo(Hz)</th>\n"," <th>MDVP:Fhi(Hz)</th>\n"," <th>MDVP:Flo(Hz)</th>\n"," <th>MDVP:Jitter(%)</th>\n"," <th>MDVP:Jitter(Abs)</th>\n"," <th>MDVP:RAP</th>\n"," <th>MDVP:PPQ</th>\n"," <th>Jitter:DDP</th>\n"," <th>MDVP:Shimmer</th>\n"," <th>MDVP:Shimmer(dB)</th>\n"," <th>...</th>\n"," <th>Shimmer:DDA</th>\n"," <th>NHR</th>\n"," <th>HNR</th>\n"," <th>status</th>\n"," <th>RPDE</th>\n"," <th>DFA</th>\n"," <th>spread1</th>\n"," <th>spread2</th>\n"," <th>D2</th>\n"," <th>PPE</th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>count</th>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>...</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," <td>195.000000</td>\n"," </tr>\n"," <tr>\n"," <th>mean</th>\n"," <td>154.228641</td>\n"," <td>197.104918</td>\n"," <td>116.324631</td>\n"," <td>0.006220</td>\n"," <td>0.000044</td>\n"," <td>0.003306</td>\n"," <td>0.003446</td>\n"," <td>0.009920</td>\n"," <td>0.029709</td>\n"," <td>0.282251</td>\n"," <td>...</td>\n"," <td>0.046993</td>\n"," <td>0.024847</td>\n"," <td>21.885974</td>\n"," <td>0.753846</td>\n"," <td>0.498536</td>\n"," <td>0.718099</td>\n"," <td>-5.684397</td>\n"," <td>0.226510</td>\n"," <td>2.381826</td>\n"," <td>0.206552</td>\n"," </tr>\n"," <tr>\n"," <th>std</th>\n"," <td>41.390065</td>\n"," <td>91.491548</td>\n"," <td>43.521413</td>\n"," <td>0.004848</td>\n"," <td>0.000035</td>\n"," <td>0.002968</td>\n"," <td>0.002759</td>\n"," <td>0.008903</td>\n"," <td>0.018857</td>\n"," <td>0.194877</td>\n"," <td>...</td>\n"," <td>0.030459</td>\n"," <td>0.040418</td>\n"," <td>4.425764</td>\n"," <td>0.431878</td>\n"," <td>0.103942</td>\n"," <td>0.055336</td>\n"," <td>1.090208</td>\n"," <td>0.083406</td>\n"," <td>0.382799</td>\n"," <td>0.090119</td>\n"," </tr>\n"," <tr>\n"," <th>min</th>\n"," <td>88.333000</td>\n"," <td>102.145000</td>\n"," <td>65.476000</td>\n"," <td>0.001680</td>\n"," <td>0.000007</td>\n"," <td>0.000680</td>\n"," <td>0.000920</td>\n"," <td>0.002040</td>\n"," <td>0.009540</td>\n"," <td>0.085000</td>\n"," <td>...</td>\n"," <td>0.013640</td>\n"," <td>0.000650</td>\n"," <td>8.441000</td>\n"," <td>0.000000</td>\n"," <td>0.256570</td>\n"," <td>0.574282</td>\n"," <td>-7.964984</td>\n"," <td>0.006274</td>\n"," <td>1.423287</td>\n"," <td>0.044539</td>\n"," </tr>\n"," <tr>\n"," <th>25%</th>\n"," <td>117.572000</td>\n"," <td>134.862500</td>\n"," <td>84.291000</td>\n"," <td>0.003460</td>\n"," <td>0.000020</td>\n"," <td>0.001660</td>\n"," <td>0.001860</td>\n"," <td>0.004985</td>\n"," <td>0.016505</td>\n"," <td>0.148500</td>\n"," <td>...</td>\n"," <td>0.024735</td>\n"," <td>0.005925</td>\n"," <td>19.198000</td>\n"," <td>1.000000</td>\n"," <td>0.421306</td>\n"," <td>0.674758</td>\n"," <td>-6.450096</td>\n"," <td>0.174351</td>\n"," <td>2.099125</td>\n"," <td>0.137451</td>\n"," </tr>\n"," <tr>\n"," <th>50%</th>\n"," <td>148.790000</td>\n"," <td>175.829000</td>\n"," <td>104.315000</td>\n"," <td>0.004940</td>\n"," <td>0.000030</td>\n"," <td>0.002500</td>\n"," <td>0.002690</td>\n"," <td>0.007490</td>\n"," <td>0.022970</td>\n"," <td>0.221000</td>\n"," <td>...</td>\n"," <td>0.038360</td>\n"," <td>0.011660</td>\n"," <td>22.085000</td>\n"," <td>1.000000</td>\n"," <td>0.495954</td>\n"," <td>0.722254</td>\n"," <td>-5.720868</td>\n"," <td>0.218885</td>\n"," <td>2.361532</td>\n"," <td>0.194052</td>\n"," </tr>\n"," <tr>\n"," <th>75%</th>\n"," <td>182.769000</td>\n"," <td>224.205500</td>\n"," <td>140.018500</td>\n"," <td>0.007365</td>\n"," <td>0.000060</td>\n"," <td>0.003835</td>\n"," <td>0.003955</td>\n"," <td>0.011505</td>\n"," <td>0.037885</td>\n"," <td>0.350000</td>\n"," <td>...</td>\n"," <td>0.060795</td>\n"," <td>0.025640</td>\n"," <td>25.075500</td>\n"," <td>1.000000</td>\n"," <td>0.587562</td>\n"," <td>0.761881</td>\n"," <td>-5.046192</td>\n"," <td>0.279234</td>\n"," <td>2.636456</td>\n"," <td>0.252980</td>\n"," </tr>\n"," <tr>\n"," <th>max</th>\n"," <td>260.105000</td>\n"," <td>592.030000</td>\n"," <td>239.170000</td>\n"," <td>0.033160</td>\n"," <td>0.000260</td>\n"," <td>0.021440</td>\n"," <td>0.019580</td>\n"," <td>0.064330</td>\n"," <td>0.119080</td>\n"," <td>1.302000</td>\n"," <td>...</td>\n"," <td>0.169420</td>\n"," <td>0.314820</td>\n"," <td>33.047000</td>\n"," <td>1.000000</td>\n"," <td>0.685151</td>\n"," <td>0.825288</td>\n"," <td>-2.434031</td>\n"," <td>0.450493</td>\n"," <td>3.671155</td>\n"," <td>0.527367</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>8 rows × 23 columns</p>\n","</div>\n"," <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b83bb5a5-5785-498f-b146-d62b868ce2a6')\"\n"," title=\"Convert this dataframe to an interactive table.\"\n"," style=\"display:none;\">\n"," \n"," <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n"," width=\"24px\">\n"," <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n"," <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 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#D2E3FC;\n"," }\n","\n"," [theme=dark] .colab-df-convert:hover {\n"," background-color: #434B5C;\n"," box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n"," filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n"," fill: #FFFFFF;\n"," }\n"," </style>\n","\n"," <script>\n"," const buttonEl =\n"," document.querySelector('#df-b83bb5a5-5785-498f-b146-d62b868ce2a6 button.colab-df-convert');\n"," buttonEl.style.display =\n"," google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n"," async function convertToInteractive(key) {\n"," const element = document.querySelector('#df-b83bb5a5-5785-498f-b146-d62b868ce2a6');\n"," const dataTable =\n"," await google.colab.kernel.invokeFunction('convertToInteractive',\n"," [key], {});\n"," if (!dataTable) return;\n","\n"," const docLinkHtml = 'Like what you see? Visit the ' +\n"," '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n"," + ' to learn more about interactive tables.';\n"," element.innerHTML = '';\n"," dataTable['output_type'] = 'display_data';\n"," await google.colab.output.renderOutput(dataTable, element);\n"," const docLink = document.createElement('div');\n"," docLink.innerHTML = docLinkHtml;\n"," element.appendChild(docLink);\n"," }\n"," </script>\n"," </div>\n"," </div>\n"," "]},"metadata":{},"execution_count":7}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3O8AclzwExyH","executionInfo":{"status":"ok","timestamp":1653200308701,"user_tz":-330,"elapsed":21,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"6a330028-c2a3-431a-f1cb-b529137cdcc7"},"source":["# distribution of target Variable\n","parkinsons_data['status'].value_counts()"],"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1 147\n","0 48\n","Name: status, dtype: int64"]},"metadata":{},"execution_count":8}]},{"cell_type":"markdown","metadata":{"id":"L1srlxtEFYfN"},"source":["1 --> Parkinson's Positive\n","\n","0 --> Healthy\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":237},"id":"zUrPan7CFTMq","executionInfo":{"status":"ok","timestamp":1653200308702,"user_tz":-330,"elapsed":18,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"9addca6f-f25f-4cde-aa11-266fbece8b9f"},"source":["# grouping the data bas3ed on the target variable\n","parkinsons_data.groupby('status').mean()"],"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":[" MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) \\\n","status \n","0 181.937771 223.636750 145.207292 0.003866 \n","1 145.180762 188.441463 106.893558 0.006989 \n","\n"," MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer \\\n","status \n","0 0.000023 0.001925 0.002056 0.005776 0.017615 \n","1 0.000051 0.003757 0.003900 0.011273 0.033658 \n","\n"," MDVP:Shimmer(dB) ... MDVP:APQ Shimmer:DDA NHR HNR \\\n","status ... \n","0 0.162958 ... 0.013305 0.028511 0.011483 24.678750 \n","1 0.321204 ... 0.027600 0.053027 0.029211 20.974048 \n","\n"," RPDE DFA spread1 spread2 D2 PPE \n","status \n","0 0.442552 0.695716 -6.759264 0.160292 2.154491 0.123017 \n","1 0.516816 0.725408 -5.333420 0.248133 2.456058 0.233828 \n","\n","[2 rows x 22 columns]"],"text/html":["\n"," <div id=\"df-2223dde4-4970-4602-b034-347b3317c577\">\n"," <div class=\"colab-df-container\">\n"," <div>\n","<style scoped>\n"," .dataframe tbody tr th:only-of-type {\n"," vertical-align: middle;\n"," }\n","\n"," .dataframe tbody tr th {\n"," vertical-align: top;\n"," }\n","\n"," .dataframe thead th {\n"," text-align: right;\n"," }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n"," <thead>\n"," <tr style=\"text-align: right;\">\n"," <th></th>\n"," <th>MDVP:Fo(Hz)</th>\n"," <th>MDVP:Fhi(Hz)</th>\n"," <th>MDVP:Flo(Hz)</th>\n"," <th>MDVP:Jitter(%)</th>\n"," <th>MDVP:Jitter(Abs)</th>\n"," <th>MDVP:RAP</th>\n"," <th>MDVP:PPQ</th>\n"," <th>Jitter:DDP</th>\n"," <th>MDVP:Shimmer</th>\n"," <th>MDVP:Shimmer(dB)</th>\n"," <th>...</th>\n"," <th>MDVP:APQ</th>\n"," <th>Shimmer:DDA</th>\n"," <th>NHR</th>\n"," <th>HNR</th>\n"," <th>RPDE</th>\n"," <th>DFA</th>\n"," <th>spread1</th>\n"," <th>spread2</th>\n"," <th>D2</th>\n"," <th>PPE</th>\n"," </tr>\n"," <tr>\n"," <th>status</th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," <th></th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>0</th>\n"," <td>181.937771</td>\n"," <td>223.636750</td>\n"," <td>145.207292</td>\n"," <td>0.003866</td>\n"," <td>0.000023</td>\n"," <td>0.001925</td>\n"," <td>0.002056</td>\n"," <td>0.005776</td>\n"," <td>0.017615</td>\n"," <td>0.162958</td>\n"," <td>...</td>\n"," <td>0.013305</td>\n"," <td>0.028511</td>\n"," <td>0.011483</td>\n"," <td>24.678750</td>\n"," <td>0.442552</td>\n"," <td>0.695716</td>\n"," <td>-6.759264</td>\n"," <td>0.160292</td>\n"," <td>2.154491</td>\n"," <td>0.123017</td>\n"," </tr>\n"," <tr>\n"," <th>1</th>\n"," <td>145.180762</td>\n"," <td>188.441463</td>\n"," <td>106.893558</td>\n"," <td>0.006989</td>\n"," <td>0.000051</td>\n"," <td>0.003757</td>\n"," <td>0.003900</td>\n"," <td>0.011273</td>\n"," <td>0.033658</td>\n"," <td>0.321204</td>\n"," <td>...</td>\n"," <td>0.027600</td>\n"," <td>0.053027</td>\n"," <td>0.029211</td>\n"," <td>20.974048</td>\n"," <td>0.516816</td>\n"," <td>0.725408</td>\n"," <td>-5.333420</td>\n"," <td>0.248133</td>\n"," <td>2.456058</td>\n"," <td>0.233828</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>2 rows × 22 columns</p>\n","</div>\n"," <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2223dde4-4970-4602-b034-347b3317c577')\"\n"," title=\"Convert this dataframe to an interactive table.\"\n"," style=\"display:none;\">\n"," \n"," <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n"," width=\"24px\">\n"," <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n"," <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n"," </svg>\n"," </button>\n"," \n"," <style>\n"," .colab-df-container {\n"," display:flex;\n"," flex-wrap:wrap;\n"," gap: 12px;\n"," }\n","\n"," .colab-df-convert {\n"," background-color: #E8F0FE;\n"," border: none;\n"," border-radius: 50%;\n"," cursor: pointer;\n"," display: none;\n"," fill: #1967D2;\n"," height: 32px;\n"," padding: 0 0 0 0;\n"," width: 32px;\n"," }\n","\n"," .colab-df-convert:hover {\n"," background-color: #E2EBFA;\n"," box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n"," fill: #174EA6;\n"," }\n","\n"," [theme=dark] .colab-df-convert {\n"," background-color: #3B4455;\n"," fill: #D2E3FC;\n"," }\n","\n"," [theme=dark] .colab-df-convert:hover {\n"," background-color: #434B5C;\n"," box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n"," filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n"," fill: #FFFFFF;\n"," }\n"," </style>\n","\n"," <script>\n"," const buttonEl =\n"," document.querySelector('#df-2223dde4-4970-4602-b034-347b3317c577 button.colab-df-convert');\n"," buttonEl.style.display =\n"," google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n"," async function convertToInteractive(key) {\n"," const element = document.querySelector('#df-2223dde4-4970-4602-b034-347b3317c577');\n"," const dataTable =\n"," await google.colab.kernel.invokeFunction('convertToInteractive',\n"," [key], {});\n"," if (!dataTable) return;\n","\n"," const docLinkHtml = 'Like what you see? Visit the ' +\n"," '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n"," + ' to learn more about interactive tables.';\n"," element.innerHTML = '';\n"," dataTable['output_type'] = 'display_data';\n"," await google.colab.output.renderOutput(dataTable, element);\n"," const docLink = document.createElement('div');\n"," docLink.innerHTML = docLinkHtml;\n"," element.appendChild(docLink);\n"," }\n"," </script>\n"," </div>\n"," </div>\n"," "]},"metadata":{},"execution_count":9}]},{"cell_type":"markdown","metadata":{"id":"8RY6c0waGSs7"},"source":["Data Pre-Processing"]},{"cell_type":"markdown","metadata":{"id":"We7sRYu7Gc4q"},"source":["Separating the features & Target"]},{"cell_type":"code","metadata":{"id":"UAcz8jFnFuzH","executionInfo":{"status":"ok","timestamp":1653200308702,"user_tz":-330,"elapsed":16,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["X = parkinsons_data.drop(columns=['name','status'], axis=1)\n","Y = parkinsons_data['status']"],"execution_count":10,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"guRof_8WG1Yn","executionInfo":{"status":"ok","timestamp":1653200308702,"user_tz":-330,"elapsed":16,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"531b55ec-5615-47e6-dde6-51295bfe8945"},"source":["print(X)"],"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":[" MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) \\\n","0 119.992 157.302 74.997 0.00784 \n","1 122.400 148.650 113.819 0.00968 \n","2 116.682 131.111 111.555 0.01050 \n","3 116.676 137.871 111.366 0.00997 \n","4 116.014 141.781 110.655 0.01284 \n",".. ... ... ... ... \n","190 174.188 230.978 94.261 0.00459 \n","191 209.516 253.017 89.488 0.00564 \n","192 174.688 240.005 74.287 0.01360 \n","193 198.764 396.961 74.904 0.00740 \n","194 214.289 260.277 77.973 0.00567 \n","\n"," MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer \\\n","0 0.00007 0.00370 0.00554 0.01109 0.04374 \n","1 0.00008 0.00465 0.00696 0.01394 0.06134 \n","2 0.00009 0.00544 0.00781 0.01633 0.05233 \n","3 0.00009 0.00502 0.00698 0.01505 0.05492 \n","4 0.00011 0.00655 0.00908 0.01966 0.06425 \n",".. ... ... ... ... ... \n","190 0.00003 0.00263 0.00259 0.00790 0.04087 \n","191 0.00003 0.00331 0.00292 0.00994 0.02751 \n","192 0.00008 0.00624 0.00564 0.01873 0.02308 \n","193 0.00004 0.00370 0.00390 0.01109 0.02296 \n","194 0.00003 0.00295 0.00317 0.00885 0.01884 \n","\n"," MDVP:Shimmer(dB) ... MDVP:APQ Shimmer:DDA NHR HNR RPDE \\\n","0 0.426 ... 0.02971 0.06545 0.02211 21.033 0.414783 \n","1 0.626 ... 0.04368 0.09403 0.01929 19.085 0.458359 \n","2 0.482 ... 0.03590 0.08270 0.01309 20.651 0.429895 \n","3 0.517 ... 0.03772 0.08771 0.01353 20.644 0.434969 \n","4 0.584 ... 0.04465 0.10470 0.01767 19.649 0.417356 \n",".. ... ... ... ... ... ... ... \n","190 0.405 ... 0.02745 0.07008 0.02764 19.517 0.448439 \n","191 0.263 ... 0.01879 0.04812 0.01810 19.147 0.431674 \n","192 0.256 ... 0.01667 0.03804 0.10715 17.883 0.407567 \n","193 0.241 ... 0.01588 0.03794 0.07223 19.020 0.451221 \n","194 0.190 ... 0.01373 0.03078 0.04398 21.209 0.462803 \n","\n"," DFA spread1 spread2 D2 PPE \n","0 0.815285 -4.813031 0.266482 2.301442 0.284654 \n","1 0.819521 -4.075192 0.335590 2.486855 0.368674 \n","2 0.825288 -4.443179 0.311173 2.342259 0.332634 \n","3 0.819235 -4.117501 0.334147 2.405554 0.368975 \n","4 0.823484 -3.747787 0.234513 2.332180 0.410335 \n",".. ... ... ... ... ... \n","190 0.657899 -6.538586 0.121952 2.657476 0.133050 \n","191 0.683244 -6.195325 0.129303 2.784312 0.168895 \n","192 0.655683 -6.787197 0.158453 2.679772 0.131728 \n","193 0.643956 -6.744577 0.207454 2.138608 0.123306 \n","194 0.664357 -5.724056 0.190667 2.555477 0.148569 \n","\n","[195 rows x 22 columns]\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xSNrvkJoG3cY","executionInfo":{"status":"ok","timestamp":1653200308703,"user_tz":-330,"elapsed":14,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"db156ede-5d9e-4ab4-de6d-ead138a71faf"},"source":["print(Y)"],"execution_count":12,"outputs":[{"output_type":"stream","name":"stdout","text":["0 1\n","1 1\n","2 1\n","3 1\n","4 1\n"," ..\n","190 0\n","191 0\n","192 0\n","193 0\n","194 0\n","Name: status, Length: 195, dtype: int64\n"]}]},{"cell_type":"markdown","metadata":{"id":"WDeqEaaHHBAS"},"source":["Splitting the data to training data & Test data"]},{"cell_type":"code","metadata":{"id":"4c6nrCiVG6NB","executionInfo":{"status":"ok","timestamp":1653200309503,"user_tz":-330,"elapsed":810,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=2)"],"execution_count":13,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"6OqUka96H35c","executionInfo":{"status":"ok","timestamp":1653200309504,"user_tz":-330,"elapsed":16,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"47eb1e86-5aa5-41f1-deb2-e02d9d2bffe7"},"source":["print(X.shape, X_train.shape, X_test.shape)"],"execution_count":14,"outputs":[{"output_type":"stream","name":"stdout","text":["(195, 22) (156, 22) (39, 22)\n"]}]},{"cell_type":"markdown","metadata":{"id":"QIOAtx35JUMg"},"source":["Model Training"]},{"cell_type":"markdown","metadata":{"id":"fWlsaBNuJV5g"},"source":["Support Vector Machine Model"]},{"cell_type":"code","metadata":{"id":"IDInA1u5JCZ9","executionInfo":{"status":"ok","timestamp":1653200309504,"user_tz":-330,"elapsed":16,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["model = svm.SVC(kernel='linear')"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"F01DNpqWKmaW","executionInfo":{"status":"ok","timestamp":1653200309505,"user_tz":-330,"elapsed":16,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"a681ba26-aa79-4b09-a0a3-ddd653726c52"},"source":["# training the SVM model with training data\n","model.fit(X_train, Y_train)"],"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["SVC(kernel='linear')"]},"metadata":{},"execution_count":16}]},{"cell_type":"markdown","metadata":{"id":"1z_-nZfuLJrH"},"source":["Model Evaluation"]},{"cell_type":"markdown","metadata":{"id":"Rj3XAnF8LMF4"},"source":["Accuracy Score"]},{"cell_type":"code","metadata":{"id":"5LwxNgnqK1Za","executionInfo":{"status":"ok","timestamp":1653200309505,"user_tz":-330,"elapsed":14,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["# accuracy score on training data\n","X_train_prediction = model.predict(X_train)\n","training_data_accuracy = accuracy_score(Y_train, X_train_prediction)"],"execution_count":17,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-dS9tcGdLm41","executionInfo":{"status":"ok","timestamp":1653200309506,"user_tz":-330,"elapsed":15,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"bbc0b0cd-ed16-4430-f137-8fdaf1f2183d"},"source":["print('Accuracy score of training data : ', training_data_accuracy)"],"execution_count":18,"outputs":[{"output_type":"stream","name":"stdout","text":["Accuracy score of training data : 0.8717948717948718\n"]}]},{"cell_type":"code","metadata":{"id":"rNUO2uHmLtjY","executionInfo":{"status":"ok","timestamp":1653200309506,"user_tz":-330,"elapsed":14,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["# accuracy score on training data\n","X_test_prediction = model.predict(X_test)\n","test_data_accuracy = accuracy_score(Y_test, X_test_prediction)"],"execution_count":19,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BsF3UnQ2L_aR","executionInfo":{"status":"ok","timestamp":1653200309506,"user_tz":-330,"elapsed":14,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"80347c36-1481-4ba3-9cf3-7ed635ca5a85"},"source":["print('Accuracy score of test data : ', test_data_accuracy)"],"execution_count":20,"outputs":[{"output_type":"stream","name":"stdout","text":["Accuracy score of test data : 0.8717948717948718\n"]}]},{"cell_type":"markdown","metadata":{"id":"QlR4JG4YMfOR"},"source":["Building a Predictive System"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"w0FjSoO1MGBU","executionInfo":{"status":"ok","timestamp":1653200309507,"user_tz":-330,"elapsed":13,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"a4715754-198f-4927-9df3-e8a104a9b154"},"source":["input_data = (197.07600,206.89600,192.05500,0.00289,0.00001,0.00166,0.00168,0.00498,0.01098,0.09700,0.00563,0.00680,0.00802,0.01689,0.00339,26.77500,0.422229,0.741367,-7.348300,0.177551,1.743867,0.085569)\n","\n","# changing input data to a numpy array\n","input_data_as_numpy_array = np.asarray(input_data)\n","\n","# reshape the numpy array\n","input_data_reshaped = input_data_as_numpy_array.reshape(1,-1)\n","\n","prediction = model.predict(input_data_reshaped)\n","print(prediction)\n","\n","\n","if (prediction[0] == 0):\n"," print(\"The Person does not have Parkinsons Disease\")\n","\n","else:\n"," print(\"The Person has Parkinsons\")\n"],"execution_count":21,"outputs":[{"output_type":"stream","name":"stdout","text":["[0]\n","The Person does not have Parkinsons Disease\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/sklearn/base.py:451: UserWarning: X does not have valid feature names, but SVC was fitted with feature names\n"," \"X does not have valid feature names, but\"\n"]}]},{"cell_type":"markdown","metadata":{"id":"FCHCMHpshHU4"},"source":["Saving the trained model"]},{"cell_type":"code","metadata":{"id":"cdmTOR4MhHCB","executionInfo":{"status":"ok","timestamp":1653200309507,"user_tz":-330,"elapsed":12,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["import pickle"],"execution_count":22,"outputs":[]},{"cell_type":"code","metadata":{"id":"4gN09lokhKuZ","executionInfo":{"status":"ok","timestamp":1653200309508,"user_tz":-330,"elapsed":13,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["filename = 'parkinsons_model.sav'\n","pickle.dump(model, open(filename, 'wb'))"],"execution_count":23,"outputs":[]},{"cell_type":"code","metadata":{"id":"IKW4D5CqhP5X","executionInfo":{"status":"ok","timestamp":1653200309510,"user_tz":-330,"elapsed":14,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"source":["# loading the saved model\n","loaded_model = pickle.load(open('parkinsons_model.sav', 'rb'))"],"execution_count":24,"outputs":[]},{"cell_type":"code","source":["for column in X.columns:\n"," print(column)"],"metadata":{"id":"m8FO1U8hRVm_","executionInfo":{"status":"ok","timestamp":1653200309511,"user_tz":-330,"elapsed":15,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}},"outputId":"079be68d-fb39-4544-9100-c6388b397091","colab":{"base_uri":"https://localhost:8080/"}},"execution_count":25,"outputs":[{"output_type":"stream","name":"stdout","text":["MDVP:Fo(Hz)\n","MDVP:Fhi(Hz)\n","MDVP:Flo(Hz)\n","MDVP:Jitter(%)\n","MDVP:Jitter(Abs)\n","MDVP:RAP\n","MDVP:PPQ\n","Jitter:DDP\n","MDVP:Shimmer\n","MDVP:Shimmer(dB)\n","Shimmer:APQ3\n","Shimmer:APQ5\n","MDVP:APQ\n","Shimmer:DDA\n","NHR\n","HNR\n","RPDE\n","DFA\n","spread1\n","spread2\n","D2\n","PPE\n"]}]},{"cell_type":"code","source":[""],"metadata":{"id":"JPyuHFeDRXZU","executionInfo":{"status":"ok","timestamp":1653200309512,"user_tz":-330,"elapsed":15,"user":{"displayName":"siddhardh selvam","userId":"13966379820454708749"}}},"execution_count":25,"outputs":[]}]}