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

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

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

Public Member Functions

def __init__
 
def getMethod
 
def getResult
 
def setResult
 
def clone
 
def compute
 
- Public Member Functions inherited from AlgorithmImpl
def computeNoThrow
 
def compute
 
def checkComputeParams
 
def checkResult
 
def setupCompute
 
def resetCompute
 
def enableResetOnCompute
 
def hostApp
 
def setHostApp
 
- Public Member Functions inherited from Algorithm
def checkComputeParams
 
def getBaseParameter
 
- Public Member Functions inherited from AlgorithmIfaceImpl
def enableChecks
 
def isChecksEnabled
 
- Public Member Functions inherited from AlgorithmIface
def checkComputeParams
 
def checkResult
 
def getMethod
 

Static Public Attributes

 parameter = ...
 
 input = ...
 

Detailed Description

Parameters
fptypeData type to use in intermediate computations of initial clusters for K-Means algorithm, double or float
methodMethod of computing initial clusters for the algorithm, Method
Enumerations
  • Method Methods of computing initial clusters for K-Means algorithm
  • InputId Identifiers of input objects for computing initial clusters for K-Means algorithm
  • ResultId Identifiers of results of computing initial clusters for K-Means algorithm
Aliases
  • Batch_Float64DeterministicDense is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.deterministicDense)
  • Batch_Float64RandomDense is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.randomDense)
  • Batch_Float64PlusPlusDense is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.plusPlusDense)
  • Batch_Float64RandomCSR is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.randomCSR)
  • Batch_Float64ParallelPlusDense is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.parallelPlusDense)
  • Batch_Float64ParallelPlusCSR is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.parallelPlusCSR)
  • Batch_Float64DeterministicCSR is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.deterministicCSR)
  • Batch_Float64PlusPlusCSR is an alias of Batch(fptype=float64, method=daal.algorithms.kmeans.init.plusPlusCSR)
  • Batch_Float32DeterministicDense is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.deterministicDense)
  • Batch_Float32RandomDense is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.randomDense)
  • Batch_Float32PlusPlusDense is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.plusPlusDense)
  • Batch_Float32RandomCSR is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.randomCSR)
  • Batch_Float32ParallelPlusDense is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.parallelPlusDense)
  • Batch_Float32ParallelPlusCSR is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.parallelPlusCSR)
  • Batch_Float32DeterministicCSR is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.deterministicCSR)
  • Batch_Float32PlusPlusCSR is an alias of Batch(fptype=float32, method=daal.algorithms.kmeans.init.plusPlusCSR)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Main constructor

Parameters
nClustersNumber of clusters

Variant 2

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

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

Member Function Documentation

def clone (   self)

Returns a pointer to the newly allocated algorithm that computes initial clusters for K-Means algorithm with a copy of input objects and parameters of this algorithm

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

Invokes computations

def getMethod (   self)

Returns the method of the algorithm

Returns
Method of the algorithm
def getResult (   self)

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

Returns
Structure that contains the results of computing initial clusters for K-Means algorithm
def setResult (   self,
  result 
)

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

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

Member Data Documentation

input = ...
static

Input data structure

parameter = ...
static

Parameters


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

For more complete information about compiler optimizations, see our Optimization Notice.