Online Processing

You can use the Naïve Bayes classifier algorithm in the online processing mode only at the training stage.

This computation mode assumes that the data arrives in blocks i = 1, 2, 3, …, nblocks.

Training

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

Naïve Bayes classifier in the online processing mode accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.

Input ID

Input

data

Pointer to the ni x p numeric table that represents the current data block. This table can be an object of any class derived from NumericTable.

labels

Pointer to the ni x 1 numeric table with class labels associated with the current data block. This table can be an object of any class derived from NumericTable.

Naïve Bayes classifier in the online processing mode 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.

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

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