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	$LaTex Math image.$	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.

In This Topic

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.