- 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”.
Example: spam/ham classification