News Article Classifier

Overview

This project involves classifying BBC News headlines into their respective categories (Tech, Entertainment, Sports, Politics, and Business). The classification is achieved through custom implementations of Naive Bayes and Support Vector Machine (SVM) classifiers.

Features

• Dataset:
  • Used the BBC News dataset containing categories and corresponding headlines.
• Preprocessing:
  • Applied Natural Language Processing (NLP) technique such as word tokenization.
  • Utilized pickling to save processed data for efficient reuse.
• Custom Implementations:
  • Naive Bayes classifier developed from scratch.
  • Support Vector Machine (SVM) classifier implemented from scratch.
• Model Comparison:
  • Generated performance comparison graphs for the implemented classifiers.

Installation

1. Clone the repository:

   https://github.com/KoushikReddy9963/News-Article-Classifier.git

2. Enter the directory:

   cd News-Article-Classifier

3. Install dependencies:

   pip install pickle
   pip install numpy
   pip install pandas
   pip install nltk
   pip install seaborn
   pip install matplotlib
   pip install sklearn
   

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