Developer Guide for Intel® Data Analytics Acceleration Library 2016 Update 4
SVM classifier follows the general workflow described in Usage Model: Training and Prediction.
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 |
double |
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. |
|
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. |
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 |
double |
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. |
|
kernel |
Pointer to object of the KernelIface class |
The kernel function. By default, the algorithm uses a linear kernel. |
|
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 |