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:

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.

Prediction

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

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.