Java* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5

Static Public Attributes | List of all members
InitMethod Class Reference

Methods of computing initial clusters for the K-Means algorithm. More...

Class Constructor

InitMethod ( int  value)

Constructs the initialization method object using the provided value

Parameters
valueValue corresponding to the initialization method object

Static Public Attributes

static final InitMethod defaultDense = new InitMethod(DeterministicDenseValue)
 
static final InitMethod deterministicDense = new InitMethod(DeterministicDenseValue)
 
static final InitMethod randomDense = new InitMethod(RandomDenseValue)
 
static final InitMethod plusPlusDense = new InitMethod(PlusPlusDenseValue)
 
static final InitMethod parallelPlusDense = new InitMethod(ParallelPlusDenseValue)
 
static final InitMethod deterministicCSR = new InitMethod(DeterministicCSRValue)
 
static final InitMethod randomCSR = new InitMethod(RandomCSRValue)
 
static final InitMethod plusPlusCSR = new InitMethod(PlusPlusCSRValue)
 
static final InitMethod parallelPlusCSR = new InitMethod(ParallelPlusCSRValue)
 

Detailed Description

Member Function Documentation

int getValue ( )

Returns the value corresponding to the initialization method object

Returns
Value corresponding to the initialization method object

Member Data Documentation

final InitMethod defaultDense = new InitMethod(DeterministicDenseValue)
static

Default: uses first nClusters points as initial clusters

final InitMethod deterministicCSR = new InitMethod(DeterministicCSRValue)
static

Uses first nClusters points as initial clusters for data in a CSR numeric table

final InitMethod deterministicDense = new InitMethod(DeterministicDenseValue)
static

Synonym of deterministicDense

final InitMethod parallelPlusCSR = new InitMethod(ParallelPlusCSRValue)
static

Kmeans|| algorithm: scalable Kmeans++ by Bahmani et al. (2012)

final InitMethod parallelPlusDense = new InitMethod(ParallelPlusDenseValue)
static

Kmeans|| algorithm: scalable Kmeans++ by Bahmani et al. (2012)

final InitMethod plusPlusCSR = new InitMethod(PlusPlusCSRValue)
static

Kmeans++ algorithm by Arthur and Vassilvitskii (2007)

final InitMethod plusPlusDense = new InitMethod(PlusPlusDenseValue)
static

Kmeans++ algorithm by Arthur and Vassilvitskii (2007)

final InitMethod randomCSR = new InitMethod(RandomCSRValue)
static

Uses random nClusters points as initial clusters for data in a CSR numeric table

final InitMethod randomDense = new InitMethod(RandomDenseValue)
static

Uses random nClusters points as initial clusters


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

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