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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