Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Related tags

Machine LearningNaive-Bayes-Classifier
Overview

Naive-Bayes Spam Classificator

Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a spam filter from scratch that classifies messages with an accuracy greater than 90%.

Main files

This project contains 2 modules:

  • bayesian_classifier.py -- BayesianClassifier class which is used to classify whether the message is spam or ham. It also calculates model score for accuracy.
  • main.py -- main file for running the programm.

How does it work?

After running a program, Spam Classificator provides the user with 2 options:

  • to test a model on data base and get model score;
  • to test a model on statement the user inputs;

If there are many words in the statement that are not present in the database, then the program will most likely output ‘needs human classification, probably spam’.

Owner
Viktoria Maksymiuk
Viktoria Maksymiuk
GitHub Repository
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