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

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Batch< algorithmFPType, method > Class Template Reference

Algorithm class for training the naive Bayes model. More...

Class Declaration

template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
class daal::algorithms::multinomial_naive_bayes::training::interface2::Batch< algorithmFPType, method >

Template Parameters
algorithmFPTypeData type to use in intermediate computations for multinomial naive Bayes training, double or float
methodComputation method, Method
Enumerations
  • Method Training methods for the multinomial naive Bayes algorithm

Constructor & Destructor Documentation

Batch ( size_t  nClasses)
inline

Default constructor

Parameters
nClassesNumber of classes
Batch ( const Batch< algorithmFPType, method > &  other)
inline

Constructs multinomial naive Bayes training algorithm by copying input objects and parameters of another multinomial naive Bayes training algorithm

Parameters
[in]otherAn algorithm to be used as the source to initialize the input objects and parameters of the algorithm

Member Function Documentation

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

Returns a pointer to the newly allocated multinomial naive Bayes training algorithm with a copy of input objects and parameters of this multinomial naive Bayes training algorithm

Returns
Pointer to the newly allocated algorithm
InputType* getInput ( )
inline

Get input objects for the multinomial naive Bayes training algorithm

Returns
Input objects for the multinomial naive Bayes training algorithm
virtual int getMethod ( ) const
inlinevirtual

Returns method of the algorithm

Returns
Method of the algorithm
ResultPtr getResult ( )
inline

Returns the structure that contains results of Naive Bayes training

Returns
Structure that contains results of Naive Bayes training
services::Status resetResult ( )
inline

Member Data Documentation

InputType input

Input objects of the algorithm

ParameterType parameter

Parameters of the training algorithm


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

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