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A simple machine-learning framework for detecting fake news using preprocessing, feature extraction, and multiple ML models.

Project description

Fake News Framework

A simple, modular, and reusable machine-learning framework for detecting fake news using preprocessing, feature extraction, and multiple ML models.
Developed by BaByLabs.


Features

  • Clean and modular data preprocessing pipeline
  • TF-IDF feature extraction for text classification
  • Multiple ML models (Logistic Regression, Random Forest, etc.)
  • Easy-to-use predict.py script for running predictions on new text
  • Well-structured and extendable package layout
  • Ready for publishing as a Python library (PyPI-compatible)

Installation (once published to PyPI)

pip install fakenews-framework

Credit to these for our OOP-Final Project:

Fake News Detection By: Sameer Patel Source: https://www.kaggle.com/code/therealsampat/fake-news-detection

Fake News Classification By: Ahmed Hafez Source: https://www.kaggle.com/code/ahmedtronic/fake-news-classification


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