C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

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Batch< algorithmFPType, method > Class Template Reference

Provides methods to run implementations of the decision forest model-based prediction. More...

Class Declaration

template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
class daal::algorithms::decision_forest::regression::prediction::interface1::Batch< algorithmFPType, method >

Template Parameters
algorithmFPTypeData type to use in intermediate computations for decision forest model-based prediction in the batch processing mode, double or float
methodComputation method in the batch processing mode, Method
Enumerations
  • Method Computation methods for decision forest model-based prediction
References

Constructor & Destructor Documentation

◆ Batch() [1/2]

Batch ( )
inline

Default constructor

◆ Batch() [2/2]

Batch ( const Batch< algorithmFPType, method > &  other)
inline

Constructs a decision forest prediction algorithm by copying input objects and parameters of another decision forest prediction algorithm

Parameters
[in]otherAlgorithm to use as the source to initialize the input objects and parameters of the algorithm

Member Function Documentation

◆ clone()

services::SharedPtr<Batch<algorithmFPType, method> > clone ( ) const
inline

Returns a pointer to a newly allocated decision forest prediction algorithm with a copy of the input objects for this decision forest prediction algorithm

Returns
Pointer to the newly allocated algorithm

◆ getMethod()

virtual int getMethod ( ) const
inlinevirtual

Returns the method of the algorithm

Returns
Method of the algorithm

Implements AlgorithmIface.

◆ getResult()

ResultPtr getResult ( )
inline

Returns the structure that contains the result of decision forest model-based prediction

Returns
Structure that contains the result of the decision forest model-based prediction

Member Data Documentation

◆ input

InputType input

Input data structure

◆ parameter

ParameterType parameter

Parameters of prediction


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

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