Naive Bayes classification

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


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