# Post Classifier using Machine Learning

## Overview
This project is a natural language processor implemented in C++ for predictive classification using the [naive bayes algorithm](https://en.wikipedia.org/wiki/Naive_Bayes_classifier). The classifier has been tested on large .csv datasets and has demonstrated an accuracy of 87% with O(n) processing time.

## Features
- Predictive classification using Naive Bayes algorithm
- High accuracy of 87%
- Efficient processing time of O(n)
- Tested on large datasets

## Installation
To install and run the project, follow these steps:
1. Clone the repository: `git clone https://github.com/felixlu4725/Post-classifier-using-Machine-Learning.git`
2. Navigate to the project directory: `cd Post-classifier-using-Machine-Learning`
3. Compile the project: `make`
4. Run the executable: `./post_classifier`

## Usage
The project can be used to classify posts in large datasets. Simply provide the input dataset in .csv format and run the classifier to obtain the predicted classifications.

## Contact
For any questions or inquiries, please contact Felix Lu at <felixlu@umich.edu>.