Java* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 4

List of all members
Parameter Class Reference

Parameter of the iterative solver algorithm. More...

Class Constructor

Parameter ( DaalContext  context)

Constructs the parameter for the iterative solver algorithm

Parameters
contextContext to manage the parameter for the iterative solver algorithm
Parameter ( DaalContext  context,
long  cObject 
)

Constructs the parameter for the iterative solver algorithm

Parameters
contextContext to manage the iterative solver algorithm
cObjectPointer to C++ implementation of the parameter

Detailed Description

Member Function Documentation

double getAccuracyThreshold ( )

Gets the accuracy of the algorithm. The algorithm terminates when this accuracy is achieved

Returns
The accuracy of the algorithm. The algorithm terminates when this accuracy is achieved
long getBatchSize ( )

Returns the number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.

Returns
The number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.
Batch getFunction ( )

Gets objective function represented as sum of functions

Returns
Objective function represented as sum of functions
long getNIterations ( )

Gets the maximal number of iterations of the algorithm

Returns
The maximal number of iterations of the algorithm
boolean getOptionalResultRequired ( )

Gets the optionalResultRequired flag

Returns
The flag
void setAccuracyThreshold ( double  accuracyThreshold)

Sets the accuracy of the algorithm. The algorithm terminates when this accuracy is achieved

Parameters
accuracyThresholdThe accuracy of the algorithm. The algorithm terminates when this accuracy is achieved
void setBatchSize ( long  batchSize)

Sets the number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.

Parameters
batchSizeThe number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.
void setFunction ( Batch  function)

Sets objective function represented as sum of functions

Parameters
functionObjective function represented as sum of functions
void setNIterations ( long  nIterations)

Sets the maximal number of iterations of the algorithm

Parameters
nIterationsThe maximal number of iterations of the algorithm
void setOptionalResultRequired ( boolean  flag)

Sets the optionalResultRequired flag

Parameters
flagThe flag. If true, optional result is calculated

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

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