Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 1

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DistributedStep2Master Class Reference

Computes K-Means in the distributed processing mode on the master node. More...

Class Constructor

Constructs the K-Means algorithm by copying input objects and parameters of another K-Means algorithm

Parameters
contextContext to manage algorithm
otherAn algorithm to be used as the source to initialize the input objects and parameters of the algorithm
DistributedStep2Master ( DaalContext  context,
Class<?extends Number >  cls,
Method  method,
long  nClusters 
)

Constructs the K-Means algorithm

Parameters
contextContext to manage algorithm
clsData type to use in intermediate computations for the algorithm, Double.class or Float.class
methodComputation method of the algorithm, Method
nClustersNumber of clusters for the algorithm

Detailed Description

References

Member Function Documentation

DistributedStep2Master clone ( DaalContext  context)

Returns the newly allocated K-Means algorithm with a copy of input objects and parameters of this K-Means algorithm

Parameters
contextContext to manage algorithm
Returns
The newly allocated algorithm
PartialResult compute ( )

Runs the K-Means algorithm

Returns
Partial results of the K-Means algorithm
Result finalizeCompute ( )

Computes the results of the K-Means algorithm

Returns
Results of the K-Means algorithm
void setPartialResult ( PartialResult  partialResult)

Registers user-allocated memory to store partial results of the K-Means algorithm

Parameters
partialResultStructure to store partial results of the K-Means algorithm
void setResult ( Result  result)

Registers user-allocated memory to store the results of the K-Means algorithm

Parameters
resultStructure to store the results of the K-Means algorithm

Member Data Documentation

Input data

Method method

Computation method for the algorithm


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

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