Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

List of all members
Parameter Class Reference

Optional SVM algorithm parameters. More...

Class Constructor

◆ Parameter() [1/9]

Parameter ( DaalContext  context)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm

◆ Parameter() [2/9]

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function

◆ Parameter() [3/9]

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem

◆ Parameter() [4/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm

◆ Parameter() [5/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold,
double  tau 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm
tauParameter of the working set selection scheme

◆ Parameter() [6/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold,
double  tau,
long  maxIterations 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm
tauParameter of the working set selection scheme
maxIterationsMaximal number of iterations of the SVM training algorithm

◆ Parameter() [7/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold,
double  tau,
long  maxIterations,
long  cacheSize 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm
tauParameter of the working set selection scheme
maxIterationsMaximal number of iterations of the SVM training algorithm
cacheSizeSize of the cache in bytes

◆ Parameter() [8/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold,
double  tau,
long  maxIterations,
long  cacheSize,
boolean  doShrinking 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm
tauParameter of the working set selection scheme
maxIterationsMaximal number of iterations of the SVM training algorithm
cacheSizeSize of the cache in bytes
doShrinkingFlag that enables use of the shrinking optimization technique

◆ Parameter() [9/9]

Parameter ( DaalContext  context,
com.intel.daal.algorithms.kernel_function.Batch  kernel,
double  c,
double  accuracyThreshold,
double  tau,
long  maxIterations,
long  cacheSize,
boolean  doShrinking,
long  shrinkingStep 
)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm
kernelKernel function
cUpper bound in constraints of the quadratic optimization problem
accuracyThresholdAccuracy of the SVM training algorithm
tauParameter of the working set selection scheme
maxIterationsMaximal number of iterations of the SVM training algorithm
cacheSizeSize of the cache in bytes
doShrinkingFlag that enables use of the shrinking optimization technique
shrinkingStepNumber of iterations between the steps of shrinking optimization technique

Detailed Description

Member Function Documentation

◆ getAccuracyThreshold()

double getAccuracyThreshold ( )

Retrieves the accuracy of the SVM training algorithm

Returns
Accuracy of the SVM training algorithm

◆ getC()

double getC ( )

Retrieves an upper bound in constraints of the quadratic optimization problem

Returns
Upper bound in constraints of the quadratic optimization problem

◆ getCacheSize()

long getCacheSize ( )

Retrieves the size of the cache in bytes to store values of the kernel matrix.

Returns
Size of the cache in bytes

◆ getDoShrinking()

boolean getDoShrinking ( )

Retrieves the flag that enables use of the shrinking optimization technique

Returns
Flag that enables use of the shrinking optimization technique

◆ getMaxIterations()

long getMaxIterations ( )

Retrieves the maximal number of iterations of the SVM training algorithm

Returns
Maximal number of iterations of the SVM training algorithm

◆ getShrinkingStep()

long getShrinkingStep ( )

Retrieves the number of iterations between the steps of shrinking optimization technique

Returns
Number of iterations between the steps of shrinking optimization technique

◆ getTau()

double getTau ( )

Retrieves the tau parameter of the working set selection scheme

Returns
Parameter of the working set selection scheme

◆ setAccuracyThreshold()

void setAccuracyThreshold ( double  accuracyThreshold)

Sets the accuracy of the SVM training algorithm

Parameters
accuracyThresholdAccuracy of the SVM training algorithm

◆ setC()

void setC ( double  C)

Sets an upper bound in constraints of the quadratic optimization problem

Parameters
CUpper bound in constraints of the quadratic optimization problem

◆ setCacheSize()

void setCacheSize ( long  cacheSize)

Sets the size of the cache in bytes to store values of the kernel matrix. A non-zero value enables use of a cache optimization technique

Parameters
cacheSizeSize of the cache in bytes

◆ setDoShrinking()

void setDoShrinking ( boolean  doShrinking)

Sets the flag that enables use of the shrinking optimization technique

Parameters
doShrinkingFlag that enables use of the shrinking optimization technique

◆ setKernel()

Sets the kernel function

Parameters
kernelKernel function

◆ setMaxIterations()

void setMaxIterations ( long  maxIterations)

Sets the maximal number of iterations of the SVM training algorithm

Parameters
maxIterationsMaximal number of iterations of the SVM training algorithm

◆ setShrinkingStep()

void setShrinkingStep ( long  shrinkingStep)

Sets the number of iterations between the steps of shrinking optimization technique

Parameters
shrinkingStepNumber of iterations between the steps of shrinking optimization technique

◆ setTau()

void setTau ( double  tau)

Sets the tau parameter of the working set selection scheme

Parameters
tauParameter of the working set selection scheme

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

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