/ML-NaiveBayes

Implementation of Naive Bayes Machine Learning Algorithm using Python

Primary LanguagePythonMIT LicenseMIT

ML-NaiveBayes

Implementation of Naive Bayes Machine Learning Algorithm using Python

About

Text Classification is widely used in this Internet Era. Most common examples are E-mail spam filtering, document classification, classification of reviews in an e-commerce site and so on. Naive Bayes is a simple Machine Learning Algorithm which basically helps in selecting the best hypothesis (h) in the given data (d). Bayes' Theorem states P(h|d) = (P(d|h) * P(h)) / P(d). So, this algorithm is completely based on probability. In the code we are building a NaiveBayes Text Classifier.

Applications

  1. Document Classification
  2. Spam Filtering

Pre-requisites

Download and install the following module:
1)numpy- pip install numpy
2)scipy- pip install scipy
3)sklearn- pip install sklearn

Author

Pranav Raikote