The main goal of the project is to analyse news article and determine if it is reliable or not.
In these uncertain times, correct and timely information is very necessary for us to beat the pandemic. Fake news creates a panic amongst people and it is so dangerous that it has even caused riots in past.
Thus, the effect of fake news has been growing, sometimes extending to the offline world and threatening public safety.
Hence it is very important for us to build a system which can help people filter out the authentic news from the fake one.
- Random Forest Classifier
- Accuracy: 89.89%
- F1 Score: 89.77%
- Support Vector Machine
- Accuracy: 96.08%
- F1 Score: 96.03%
- Passive Aggressive Classifier
- Accuracy: 96.41%
- F1 Score: 96.36%
After comparing different models, we concluded that Passive Aggressive Classifer works better than others.
Here is the Live Deployment