Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 2
Multi-class 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, a multi-class 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 multi-class classifier. The only training method supported so far is One-Against-One. |
|
training |
Pointer to an object of the SVM training class |
Pointer to the training algorithm of the two-class classifier. By default, the SVM two-class classifier is used. |
|
nClasses |
Not applicable |
The number of classes, a required parameter. |
For a description of the input and output, refer to Usage Model: Training and Prediction.
At the prediction stage, a multi-class classifier has the following parameters:
Parameter |
Method |
Default Value |
Description |
|
---|---|---|---|---|
algorithmFPType |
defaultDense or voteBased |
float |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
|
pmethod |
Not applicable |
defaultDense |
Available methods for multi-class classifier prediction stage:
|
|
tmethod |
defaultDense or voteBased |
training::oneAgainstOne |
The computation method that was used to train the multi-class classifier model. |
|
prediction |
defaultDense or voteBased |
Pointer to an object of the SVM prediction class |
Pointer to the prediction algorithm of the two-class classifier. By default, the SVM two-class classifier is used. |
|
nClasses |
defaultDense or voteBased |
Not applicable |
The number of classes, a required parameter. |
|
maxIterations |
defaultDense |
100 |
The maximal number of iterations for the algorithm. |
|
accuracyThreshold |
defaultDense |
1.0e-12 |
The prediction accuracy. |
C++:
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