# Fake News Classifier

Implementation of fake news classifier using TfIdf Vectorization and PassiveAgressive Classifier.

**Term Frequency (TF)**: Measures the frequency of a word within a document.

**Inverse Document Frequency (IDF)**: Measures how important a word is in the entire collection of documents.

The **TfidfVectorizer** calculates TF-IDF scores for each word in the documents, and you can use the resulting feature matrix as input for various machine-learning algorithms.

The **Passive-aggressive classifier** is an online learning algorithm used for classification tasks. The name "Passive Aggressive" reflects its behavior of being passive when predictions are correct and aggressive when they are incorrect, allowing it to quickly adjust to changing data patterns.

Dataset: [https://drive.google.com/file/d/1er9NJTLUA3qnRuyhfzuN0XUsoIC4a-\_q/view?usp=sharing](https://drive.google.com/file/d/1er9NJTLUA3qnRuyhfzuN0XUsoIC4a-_q/view?usp=sharing)

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1694019616190/fe84f103-91d3-4ce7-a7d4-a35dc7b605d3.png align="center")