Post Classifier using Machine Learning

Overview

This project is a natural language processor implemented in C++ for predictive classification using the naive bayes algorithm. 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.