Java* API Reference for Intel® Data Analytics Acceleration Library 2019

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Computes the PCA explained variance quality metrics in batch processing mode. More...

Class Constructor

Constructs the explained variance quality metrics algorithm in the batch processing mode by copying input objects and parameters of another explained variance quality metrics algorithm

Parameters
contextContext to manage the explained variance quality metrics algorithm
otherAn algorithm to be used as the source to initialize the input objects and parameters of the algorithm
ExplainedVarianceBatch ( DaalContext  context,
Class<?extends Number >  cls,
ExplainedVarianceMethod  method 
)

Constructs the explained variance quality metrics algorithm in the batch processing mode

Parameters
contextContext to manage the explained variance quality metrics algorithm
clsData type to use in intermediate computations of the explained variance quality metrics, Double.class or Float.class
methodMethod for computing the explained variance quality metrics, ExplainedVarianceMethod

Detailed Description

Enumerations
References

Member Function Documentation

ExplainedVarianceBatch clone ( DaalContext  context)

Returns the newly allocated explained variance quality metrics algorithm with a copy of input objects and parameters of this explained variance quality metrics algorithm

Parameters
contextContext to manage the explained variance quality metrics algorithm
Returns
The newly allocated algorithm

Computes the explained variance quality metrics

Returns
Structure that contains results of the explained variance quality metrics algorithm
void setResult ( ExplainedVarianceResult  result)

Registers user-allocated memory for storing results of the explained variance quality metrics algorithm

Parameters
resultStructure for storing results of the explained variance quality metrics algorithm

The documentation for this class was generated from the following file:

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