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

Predicts logistic regression results. More...

Public Member Functions

def __init__
 
def parameter
 
def getInput
 
def getMethod
 
def clone
 
def getResult
 
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 = ...
 

Detailed Description

Deprecated:
This item will be removed in a future release.
Parameters
fptypeData type to use in intermediate computations for the logistic regression algortithm, double or float
methodlogistic regression computation method, Method
Enumerations
  • Method logistic regression prediction methods
  • classifier.prediction.NumericTableInputId Identifiers of input Numeric Table objects for the logistic regression prediction algorithm
  • classifier.prediction.ModelInputId Identifiers of input Model objects of the algorithm
  • classifier.prediction.ResultId Identifiers of prediction results
References
Aliases
  • Batch_Float64DefaultDense is an alias of Batch(fptype=float64, method=daal.algorithms.logistic_regression.prediction.defaultDense)
  • Batch_Float32DefaultDense is an alias of Batch(fptype=float32, method=daal.algorithms.logistic_regression.prediction.defaultDense)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Constructs logistic regression prediction algorithm

Parameters
nClassesNumber of classes

Variant 2

Constructs a logistic regression prediction algorithm by copying input objects and parameters of another logistic regression 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 logistic regression prediction algorithm with a copy of input objects and parameters of this logistic regression prediction algorithm

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

Invokes computations

def getInput (   self)

Gets input objects for the logistic regression prediction algorithm

Returns
Input objects for the logistic regression prediction algorithm
def getMethod (   self)

Returns method of the algorithm

Returns
Method of the algorithm
def getResult (   self)

Returns the structure that contains the result of the logistic regression model-based prediction

Returns
Structure that contains the result of the logistic regression model-based prediction
def parameter (   self,
  args 
)

Variant 1

Gets parameter of the algorithm

Returns
parameter of the algorithm

Variant 2

Gets parameter of the algorithm

Returns
parameter of the algorithm

Member Data Documentation

input = ...
static

Input objects of the algorithm


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

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