Naïve Bayesian Classification Naïve assumption: attribute independence P(x 1,…,x k |C) = P(x 1 |C)·…·P(x k |C) If i-th attribute is categorical: P(x i |C) is estimated as the relative freq of samples having value x i as i-th attribute in class C If i-th attribute is continuous: – Real-valued variables discretized to create nominal versions – P(x i |C) is estimated thru a Gaussian density function Computationally feasible in both cases Generative probabilistic model with conditional independence assumption on p( x | c k ), i.e.
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