Batch Processing

Naïve Bayes classifier in the batch processing mode follows the general workflow described in Usage Model: Training and Prediction.

Training

For a description of the input and output, refer to Usage Model: Training and Prediction.

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/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

For a description of the input and output, refer to Usage Model: Training and 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.

For more complete information about compiler optimizations, see our Optimization Notice.
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