Getting Started Guide

Contents

Batch Processing

SVM classifier follows the general workflow described in Usage Model: Training and Prediction .

Training

For a description of the input and output, refer to Usage Model: Training and Prediction .
At the training stage, SVM classifier has the following parameters:
Parameter
Default Value
Description
algorithmFPType
float
The floating-point type that the algorithm uses for intermediate computations. Can be
float
or
double
.
method
defaultDense
The computation method used by the SVM classifier. The only training method supported so far is the Boser method.
nClasses
2
The number of classes.
C
1
Upper bound in conditions of the quadratic optimization problem.
accuracyThreshold
0.001
The training accuracy.
tau
1.0e-6
Tau parameter of the WSS scheme.
maxIterations
1000000
Maximal number of iterations for the algorithm.
cacheSize
8000000
Size of cache in bytes for storing values of the kernel matrix. A non-zero value enables use of a cache optimization technique.
doShrinking
true
A flag that enables use of a shrinking optimization technique.
kernel
Pointer to an object of the
KernelIface
class
The kernel function. By default, the algorithm uses a linear kernel. For details, see Kernel Functions .

Prediction

For a description of the input and output, refer to Usage Model: Training and Prediction .
At the prediction stage, SVM classifier has the following parameters:
Parameter
Default Value
Description
algorithmFPType
float
The floating-point type that the algorithm uses for intermediate computations. Can be
float
or
double
.
method
defaultDense
Performance-oriented computation method, the only prediction method supported by the algorithm.
nClasses
2
The number of classes.
kernel
Pointer to object of the
KernelIface
class
The kernel function. By default, the algorithm uses a linear kernel.
Optimization Notice
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.
Notice revision #20110804

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804