Naive Bayes Tutorial for Machine Learning

Last Updated on August 12, 2019

Naive Bayes is a very simple classification algorithm that makes some strong assumptions about the independence of each input variable.

Nevertheless, it has been shown to be effective in a large number of problem domains. In this post you will discover the Naive Bayes algorithm for categorical data. After reading this post, you will know.

• How to work with categorical data for Naive Bayes.
• How to prepare the class and conditional probabilities for a Naive Bayes model.
• How to use a learned Naive Bayes model to make predictions.

This post was written for developers and does not assume a background in statistics or probability. Open a spreadsheet and follow along. If you have any questions about Naive Bayes ask in the comments and I will do my best to answer.

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Let’s get started.