Naïve Bayes Classifier
- , where is the number of occurrences of the featurekin the classj, is the total number of occurrences of all features in the class, the (for example, ), and is the sum of all .
- , where is the prior class estimate.
- If input data is homogeneous:
- For the training data set, use a homogeneous numeric table of the same type as specified in the algorithmFPType class template parameter.
- For class labels, use a homogeneous numeric table of type int.
- If input data is non-homogeneous, use AOS layout rather than SOA layout.
- For the working data set, use a homogeneous numeric table of the same type as specified in the algorithmFPType class template parameter.
- For predicted labels, use a homogeneous numeric table of type int.
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