https://github.com/bdurga26/fake-news-detection

This project aims to find whether the given news is real or fake by using Machine learning Algorithms.
https://github.com/bdurga26/fake-news-detection

ds ml numpy pandas python sklearn

Last synced: about 1 month ago
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This project aims to find whether the given news is real or fake by using Machine learning Algorithms.

• Host: GitHub
• URL: https://github.com/bdurga26/fake-news-detection
• Owner: BDurga26
• Created: 2024-03-16T11:17:17.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-04T04:55:57.000Z (over 1 year ago)
• Last Synced: 2025-01-14T04:12:25.018Z (9 months ago)
• Topics: ds, ml, numpy, pandas, python, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 23.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
This project aims to predict whether the given news is real or fake.


It takes the news(String) as input and gives a string REAL or FAKE.


![p1](https://github.com/BDurga26/Fake-News-Detection/assets/103586967/86e4d0d6-2f88-48d7-99c7-6f9e4b763ea8)

This is the application developed using Streamlit. We can add user input to it.

![p2](https://github.com/BDurga26/Fake-News-Detection/assets/103586967/806c659b-a0d2-4795-ac20-d00acf4016b3)

The algorithms used are Logistic Regression with an accuracy of 92%.


Decision Tree with an accuracy of 79%.


Random forest with an accuracy of 89%


Naive bayes with an accuracy of 82%.


Passive Agressive with an accuracy of 93%


SVM with an accuracy of 94%.


The SVM model is saved using joblib as it gets highest accuracy and vector file which is used to convert text to numerics.