C++ API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

References | Namespaces | Classes | Functions
Support Vector Machine Classifier

Contains classes to work with the support vector machine classifier. More...

References

 Prediction
 Contains classes to make predictions based on the SVM model.
 
 Quality Metrics
 Contains classes to check the quality of the model trained with the SVM algorithm.
 
 Training
 Contains classes to train the SVM model.
 

Namespaces

 daal::algorithms::svm
 Contains classes to work with the support vector machine classifier.
 
 daal::algorithms::svm::interface1
 Contains version 1.0 of Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface.
 

Classes

struct  Parameter
 Optional parameters. More...
 
class  ModelBuilder< modelFPType >
 Model Builder class for class SVM Model. More...
 

Functions

 ModelBuilder (size_t nFeatures, size_t nSupportVectors)
 
template<typename RandomIterator >
void setSupportVectors (RandomIterator first, RandomIterator last)
 
template<typename RandomIterator >
void setSupportIndices (RandomIterator first, RandomIterator last)
 
template<typename RandomIterator >
void setClassificationCoefficients (RandomIterator first, RandomIterator last)
 
void setBias (modelFPType bias)
 
ModelPtr getModel ()
 
services::Status getStatus ()
 

Function Documentation

ModelPtr getModel ( )
inline

Get built model

Returns
Model pointer
services::Status getStatus ( )
inline

Get status of model building

Returns
Status
ModelBuilder ( size_t  nFeatures,
size_t  nSupportVectors 
)
inline

Constructs the SVM model builder

Template Parameters
modelFPTypeData type to store SVM model data, double or float
Parameters
[in]nFeaturesNumber of features in training data
[in]nSupportVectorsNumber of support vectors in model
void setBias ( modelFPType  bias)
inline

Method to set bias term to model

Parameters
[in]biasThe value to be set
void setClassificationCoefficients ( RandomIterator  first,
RandomIterator  last 
)
inline

Method to set classification coefficients to model via random access iterator

Template Parameters
RandomIteratorRandom access iterator type for access to values of classification coefficients
Parameters
[in]firstIterator which point to first element of classification coefficients
[in]lastIterator which point to last element of classification coefficients
void setSupportIndices ( RandomIterator  first,
RandomIterator  last 
)
inline

Method to set support indices to model via random access iterator

Template Parameters
RandomIteratorRandom access iterator type for access to values of suport indices
Parameters
[in]firstIterator which point to first element of support indices
[in]lastIterator which point to last element of support indices
void setSupportVectors ( RandomIterator  first,
RandomIterator  last 
)
inline

Method to set support vectors to model via random access iterator

Template Parameters
RandomIteratorRandom access iterator type for access to values of suport vectors
Parameters
[in]firstIterator which point to first element of support vectors
[in]lastIterator which point to last element of support vectors

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