Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

Public Member Functions | Static Public Attributes | List of all members
Distributed Class Reference

Computes the results of K-Means algorithm in the first step of the distributed processing mode. More...

Public Member Functions

def __init__
 
def getMethod
 
def getResult
 
def setResult
 
def getPartialResult
 
def setPartialResult
 
def checkFinalizeComputeParams
 
def clone
 
def compute
 
def finalizeCompute
 

Static Public Attributes

 input = ...
 
 parameter = ...
 

Detailed Description

Parameters
fptypeData type to use in intermediate computations of K-Means, double or float
methodComputation method of the algorithm, Method
Enumerations
  • Method Computation methods for K-Means algorithm
  • InputId Identifiers of input objects for the K-Means algorithm
  • ResultId Identifiers of results of K-Means algorithm
Aliases
  • Distributed_Step1LocalFloat64LloydCSR is an alias of Distributed(step=daal.step1Local, fptype=float64, method=daal.algorithms.kmeans.lloydCSR)
  • Distributed_Step1LocalFloat64LloydDense is an alias of Distributed(step=daal.step1Local, fptype=float64, method=daal.algorithms.kmeans.lloydDense)
  • Distributed_Step1LocalFloat32LloydCSR is an alias of Distributed(step=daal.step1Local, fptype=float32, method=daal.algorithms.kmeans.lloydCSR)
  • Distributed_Step1LocalFloat32LloydDense is an alias of Distributed(step=daal.step1Local, fptype=float32, method=daal.algorithms.kmeans.lloydDense)
  • Distributed_Step2MasterFloat64LloydCSR is an alias of Distributed(step=daal.step2Master, fptype=float64, method=daal.algorithms.kmeans.lloydCSR)
  • Distributed_Step2MasterFloat64LloydDense is an alias of Distributed(step=daal.step2Master, fptype=float64, method=daal.algorithms.kmeans.lloydDense)
  • Distributed_Step2MasterFloat32LloydCSR is an alias of Distributed(step=daal.step2Master, fptype=float32, method=daal.algorithms.kmeans.lloydCSR)
  • Distributed_Step2MasterFloat32LloydDense is an alias of Distributed(step=daal.step2Master, fptype=float32, method=daal.algorithms.kmeans.lloydDense)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Constructs K-Means algorithm

Parameters
nClustersNumber of clusters
assignFlagFlag to calculate partial assignment

Variant 2

Constructs K-Means algorithm

Parameters
nClustersNumber of clusters
assignFlagFlag to calculate partial assignment

Variant 3

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

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

Member Function Documentation

def checkFinalizeComputeParams (   self)

Validates the parameters of the finalizeCompute() method

def clone (   self)

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

Returns
Pointer to the newly allocated algorithm
def compute (   self)

Invokes computations and returns partial result

def finalizeCompute (   self)

Finalizes computations and returns (final) result

def getMethod (   self)

Returns the method of the algorithm

Returns
Method of the algorithm
def getPartialResult (   self)

Returns the structure that contains computed partial results

Returns
Structure that contains computed partial results
def getResult (   self)

Returns the structure that contains the results of K-Means algorithm

Returns
Structure that contains the results of K-Means algorithm
def setPartialResult (   self,
  partialRes 
)

Sets the structure that contains computed partial results

def setResult (   self,
  result 
)

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

Parameters
resultStructure to store the results of K-Means algorithm

Member Data Documentation

input = ...
static

Input data structure

parameter = ...
static

K-Means parameters structure


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

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