CPS News Category Classification
This repository contains code for training a news category classification model using Multinomial Naive Bayes algorithm. The goal is to classify news headlines into different categories. The project includes data preprocessing, model training, evaluation, and testing.
Prerequisites
Ensure you have the necessary libraries installed. You can do this by installing the dependencies listed in requirements.txt.
Setup
1. Clone the Repository
bash command
git clone https://github.com/your\_username/news-category-classification.git
cd news-category-classification
2. Install Dependencies
pip install -r requirements.txt
3. Download NLTK
Ensure you have the necessary NLTK data downloaded:
import nltk
nltk.download('stopwords')
nltk.download('punkt')
nltk.download('wordnet')
4. Place Data Files
Place your JSON data files in the appropriate paths. For example:
- CPS_use_case_classification_training.json for training data
- CPS_use_case_classification_response.json for test data
Usage
Running the Script
Main Script execution
python news_category_classification.py
Test Script execution
Execute the test script:
python -m unittest news_category_classification_unittest.py
Author
Shruthi Shri