Batch Processing¶

Naïve Bayes classifier in the batch processing mode follows the general workflow described in Classification Usage Model.

Training¶

At the training stage, Naïve Bayes classifier has the following parameters:

Training Parameters for Naïve Bayes Classifier (Batch Processing)¶
Parameter	Default Value	Description
`algorithmFPType`	`float`	The floating-point type that the algorithm uses for intermediate computations. Can be `float` or `double`.
`method`	`defaultDense`	Available computation methods for the Naïve Bayes classifier: `defaultDense` - default performance-oriented method `fastCSR` - performance-oriented method for CSR numeric tables
`nClasses`	Not applicable	The number of classes. A required parameter.
`priorClassEstimates`	\(1/\text{nClasses}\)	Vector of size `nClasses` that contains prior class estimates. The default value applies to each vector element.
`alpha`	\(1\)	Vector of size \(p\) that contains the imagined occurrences of features. The default value applies to each vector element.

At the prediction stage, Naïve Bayes classifier has the following parameters:

Prediction Parameters for Naïve Bayes Classifier (Batch Processing)¶
Parameter	Default Value	Description
`algorithmFPType`	`float`	The floating-point type that the algorithm uses for intermediate computations. Can be `float` or `double`.
`method`	`defaultDense`	Performance-oriented computation method, the only method supported by the algorithm.
`nClasses`	Not applicable	The number of classes. A required parameter.

Naïve Bayes Classifier

Online Processing