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

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Distributed< step2Master, algorithmFPType, method > Class Template Reference

Algorithm class for training naive Bayes final model on the second step in the distributed processing mode. More...

Class Declaration

template<typename algorithmFPType, Method method>
class daal::algorithms::multinomial_naive_bayes::training::interface2::Distributed< step2Master, algorithmFPType, method >

Template Parameters
algorithmFPTypeData type to use in intermediate computations for the multinomial naive Bayes training on the second step in distributed processing mode, double or float
methodNaive Bayes training method on the second step in distributed processing mode, Method
Enumerations
  • Method Training methods for the multinomial naive Bayes algorithm

Constructor & Destructor Documentation

Distributed ( size_t  nClasses)
inline

Default constructor

Parameters
nClassesNumber of classes
Distributed ( const Distributed< step2Master, 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::Status checkFinalizeComputeParams ( )
inline

Validates parameters of the finalizeCompute() method

Returns
Status of computations
services::SharedPtr<Distributed<step2Master, 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
virtual int getMethod ( ) const
inlinevirtual

Returns method of the algorithm

Returns
Method of the algorithm
PartialResultPtr getPartialResult ( )
inline

Returns the structure that contains computed partial results

Returns
Structure that contains computed partial results
ResultPtr getResult ( )
inline

Returns the structure that contains results of Naive Bayes training

Returns
Structure that contains results of Naive Bayes training
services::Status setPartialResult ( const PartialResultPtr &  partialResult)
inline

Registers user-allocated memory for storing partial training results

Parameters
[in]partialResultStructure for storing partial results
services::Status setResult ( const ResultPtr &  result)
inline

Registers user-allocated memory to store results of Naive Bayes training

Parameters
[in]resultStructure to store results of Naive Bayes training
Returns
Status of computations

Member Data Documentation

InputType input

Input objects of the algorithm

ParameterType parameter

Parameters of the distributed training algorithm


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

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