Naive Bayes Algorithm

The Naive Bayes (NB) algorithm is used to solve classification problems. NB makes predictions using Bayes' Theorem, which derives the probability of a prediction from the underlying evidence. NB affords fast model build and apply.

NB looks at the historical data and calculates conditional probabilities for the target values by observing the frequency of attribute values and of combinations of attribute values.

NB assumes that each attribute is independent from the others. In practice, this assumption usually does not degrade the model's predictive accuracy significantly.

For more information about NB, see the Oracle Data Mining Concepts in Where to Find More Information.