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

List of all members
Batch< algorithmFPType, method > Class Template Reference

Computes initial clusters for the K-Means algorithm in the batch processing mode. More...

Class Declaration

template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
class daal::algorithms::kmeans::init::interface1::Batch< algorithmFPType, method >

Template Parameters
algorithmFPTypeData type to use in intermediate computations of initial clusters for the K-Means algorithm, double or float
methodMethod of computing initial clusters for the algorithm, Method
Enumerations
  • Method Methods of computing initial clusters for the K-Means algorithm
  • InputId Identifiers of input objects for computing initial clusters for the K-Means algorithm
  • ResultId Identifiers of results of computing initial clusters for the K-Means algorithm

Constructor & Destructor Documentation

◆ Batch() [1/2]

Batch ( size_t  nClusters)
inline

Main constructor

Parameters
[in]nClustersNumber of clusters

◆ Batch() [2/2]

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

Constructs an algorithm that computes initial clusters for the K-Means algorithm by copying input objects and parameters of another algorithm

Parameters
[in]otherAn algorithm to be used 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 the newly allocated algorithm that computes initial clusters for the K-Means algorithm with a copy of input objects and parameters of this 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 results of computing initial clusters for the K-Means algorithm

Returns
Structure that contains the results of computing initial clusters for the K-Means algorithm

◆ setResult()

services::Status setResult ( const ResultPtr result)
inline

Registers user-allocated memory to store the results of computing initial clusters for the K-Means algorithm

Parameters
[in]resultStructure to store the results of computing initial clusters for the K-Means algorithm

Member Data Documentation

◆ input

InputType input

Input data structure

◆ parameter

ParameterType parameter

K-Means parameters structure


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

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