# 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.

## Prediction¶

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.