Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 1

List of all members

Optional SVM algorithm parameters. More...

Class Constructor

Parameter ( DaalContext  context)

Constructs a parameter

Parameters
contextContext to manage the parameter of the SVM algorithm

Constructs a parameter

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

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 ( 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 ( 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 ( 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 ( 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 ( 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 ( 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

double getAccuracyThreshold ( )

Retrieves the accuracy of the SVM training algorithm

Returns
Accuracy of the SVM training algorithm
double getC ( )

Retrieves an upper bound in constraints of the quadratic optimization problem

Returns
Upper bound in constraints of the quadratic optimization problem
long getCacheSize ( )

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

Returns
Size of the cache in bytes
boolean getDoShrinking ( )

Retrieves the flag that enables use of the shrinking optimization technique

Returns
Flag that enables use of the shrinking optimization technique
long getMaxIterations ( )

Retrieves the maximal number of iterations of the SVM training algorithm

Returns
Maximal number of iterations of the SVM training algorithm
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
double getTau ( )

Retrieves the tau parameter of the working set selection scheme

Returns
Parameter of the working set selection scheme
void setAccuracyThreshold ( double  accuracyThreshold)

Sets the accuracy of the SVM training algorithm

Parameters
accuracyThresholdAccuracy of the SVM training algorithm
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
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
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

Sets the kernel function

Parameters
kernelKernel function
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
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
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:

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