The basis

• It’s based on Bayes’ theorem (check the wikipedia link, and see how complex the decision trees could be).
• Assumes predictors contribute independently to the classification.
• Works well in supervised learning problems.
• Works with continuous and discrete data.
• Can work with discrete data sets.
• It is not sensitive to non-correlating “predictors”.

Naives Bayes plot

Example: spam/ham classification