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

Static Public Member Functions | List of all members
Model Class Reference

Model of the classifier trained by the brownboost::training::Batch algorithm. More...

Static Public Member Functions

template<typename modelFPType >
static DAAL_EXPORT
services::SharedPtr< Model
create (size_t nFeatures, services::Status *stat=NULL)
 

Class Declaration

References

Constructor & Destructor Documentation

DAAL_EXPORT Model ( size_t  nFeatures,
modelFPType  dummy 
)

Constructs the BrownBoost Model

Template Parameters
modelFPTypeData type to store BrownBoost model data, double or float
Parameters
[in]nFeaturesNumber of features in the dataset
[in]dummyDummy variable for the templated constructor
Deprecated:
This item will be removed in a future release. Use Model::create instead.
Model ( size_t  nFeatures = 0)
inline

Empty constructor for deserialization

Deprecated:
This item will be removed in a future release. Use Model::create instead.

Member Function Documentation

void addWeakLearnerModel ( classifier::ModelPtr  model)

Add weak learner model into the BrownBoost model

Parameters
[in]modelWeak learner model to add into collection
void clearWeakLearnerModels ( )

Clears the collecion of weak learners

static DAAL_EXPORT services::SharedPtr<Model> create ( size_t  nFeatures,
services::Status *  stat = NULL 
)
static

Constructs the BrownBoost model

Template Parameters
modelFPTypeData type to store BrownBoost model data, double or float
Parameters
[in]nFeaturesNumber of features in the dataset
[out]statStatus of the model construction
data_management::NumericTablePtr getAlpha ( )

Returns a pointer to the array of weights of weak learners constructed during training of the BrownBoost algorithm. The size of the array equals the number of weak learners

Returns
Array of weights of weak learners.
size_t getNumberOfFeatures ( ) const
inline

Retrieves the number of features in the dataset was used on the training stage

Returns
Number of features in the dataset was used on the training stage
size_t getNumberOfWeakLearners ( ) const

Returns the number of weak learners constructed during training of the BrownBoost algorithm

Returns
The number of weak learners
classifier::ModelPtr getWeakLearnerModel ( size_t  idx) const

Returns weak learner model constructed during training of the BrownBoost algorithm

Parameters
[in]idxIndex of the model in the collection
Returns
Weak Learner model corresponding to the index idx

The documentation for this class was generated from the following file:

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