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

Provides methods to run implementations of the multi-class classifier prediction algorithm. More...

Public Member Functions

def __init__
 
def getInput
 
def getMethod
 
def clone
 
def compute
 
- Public Member Functions inherited from Batch
def getInput
 
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

 input = ...
 
 parameter = ...
 

Detailed Description

Deprecated:
This item will be removed in a future release.
Parameters
fptypeData type to use in intermediate computations for multi-class classifier prediction algorithm, double or float
pmethodComputation method for the algorithm, prediction.Method
tmethodComputation method that was used to train the multi-class classifier model, training.Method
Enumerations
  • Method Computation methods for the multi-class classifier prediction algorithm
  • classifier.prediction.NumericTableInputId Identifiers of input NumericTable objects for the multi-class classifier prediction algorithm
  • classifier.prediction.ModelInputId Identifiers of input Model objects for the multi-class classifier prediction algorithm
  • classifier.prediction.ResultId Identifiers of the results of the multi-class classifier prediction algorithm
References
Aliases
  • Batch_Float64VoteBasedOneAgainstOne is an alias of Batch(fptype=float64, pmethod=daal.algorithms.multi_class_classifier.prediction.voteBased, tmethod=daal.algorithms.multi_class_classifier.training.oneAgainstOne)
  • Batch_Float64MultiClassClassifierWuOneAgainstOne is an alias of Batch(fptype=float64, pmethod=daal.algorithms.multi_class_classifier.prediction.multiClassClassifierWu, tmethod=daal.algorithms.multi_class_classifier.training.oneAgainstOne)
  • Batch_Float32VoteBasedOneAgainstOne is an alias of Batch(fptype=float32, pmethod=daal.algorithms.multi_class_classifier.prediction.voteBased, tmethod=daal.algorithms.multi_class_classifier.training.oneAgainstOne)
  • Batch_Float32MultiClassClassifierWuOneAgainstOne is an alias of Batch(fptype=float32, pmethod=daal.algorithms.multi_class_classifier.prediction.multiClassClassifierWu, tmethod=daal.algorithms.multi_class_classifier.training.oneAgainstOne)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Default constructor

Deprecated:
This item will be removed in a future release.

Variant 2

Default constructor

Parameters
nClassesNumber of classes

Variant 3

Constructs multi-class classifier prediction algorithm by copying input objects and parameters of another multi-class classifier prediction 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 multi-class classifier prediction algorithm with a copy of input objects and parameters of this multi-class classifier prediction algorithm

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

Invokes computations

def getInput (   self)

Get input objects for the multi-class classifier prediction algorithm

Returns
Input objects for the multi-class classifier prediction algorithm
def getMethod (   self)

Returns method of the algorithm

Returns
Method of the algorithm

Member Data Documentation

input = ...
static

Input objects of the algorithm

parameter = ...
static

Parameters of the algorithm


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

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