NaiveBayesClassifier.GetStandardDeviations Method

NaiveBayesClassifierGetStandardDeviations Method

Returns a table of standard deviations for each continuous attribute in continuousData segmented by the target classes in classificationData.

Namespace: Imsl.DataMining
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0

Syntax

C++

Copy

public double[][] GetStandardDeviations(
	double[][] continuousData,
	int[] classificationData
)

Public Function GetStandardDeviations ( 
	continuousData As Double()(),
	classificationData As Integer()
) As Double()()

public:
array<array<double>^>^ GetStandardDeviations(
	array<array<double>^>^ continuousData, 
	array<int>^ classificationData
)

member GetStandardDeviations : 
        continuousData : float[][] * 
        classificationData : int[] -> float[][]

Parameters

continuousData: Type: SystemDouble
A double matrix containing training values for the continuous attributes.
classificationData: Type: SystemInt32
An int array containing the target classifications for the training patterns.

Return Value

Type: Double
A continuousData[0].Length by nClassesdouble matrix, stdev, containing the standard deviations segmented by the target classes. The i-th row contains the standard deviation of the i-th continuous attribute for each value of the target classification. That is, stdev[i][j] is the standard deviations for the i-th continuous attribute when the target classification equals j, unless there are no training patterns for this condition.

Remarks

This method is provided as a utility, prior training is not necessary.

Reference

NaiveBayesClassifier Class

Imsl.DataMining Namespace