JMP 13 Predictive and Specialized Modeling

Naive Bayes Platform Overview

The Naive Bayes platform classifies observations into classes that are defined by the levels of a categorical response variable. The variables (or factors) that are used for classification are often called features in the data mining literature.

For each class, the naive Bayes algorithm computes the conditional probability of each feature value occurring. If a feature is continuous, its conditional marginal density is estimated. The naive Bayes technique assumes that, within a class, the features are independent. (This is the reason that the technique is referred to as “naive”.) Classification is based on the ...