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

Trains model of the logistic regression algorithms in the batch processing mode. More...

Public Member Functions

def __init__
 
def parameter
 
def getInput
 
def getMethod
 
def getResult
 
def resetResult
 
def clone
 
def compute
 
- Public Member Functions inherited from Batch
def getInput
 
def setResult
 
def getResult
 
def resetResult
 
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 logistic regression, double or float
methodlogistic regression computation method, daal.algorithms.logistic_regression.training.Method
Enumerations
  • Method logistic regression training methods
  • classifier.training.InputId Identifiers of input objects for the logistic regression training algorithm
  • classifier.training.ResultId Identifiers of logistic regression training results
References
Aliases
  • Batch_Float64DefaultDense is an alias of Batch(fptype=float64, method=daal.algorithms.logistic_regression.training.defaultDense)
  • Batch_Float32DefaultDense is an alias of Batch(fptype=float32, method=daal.algorithms.logistic_regression.training.defaultDense)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Constructs the logistic regression training algorithm

Parameters
nClassesNumber of classes
solverOptimization solver

Variant 2

Constructs the logistic regression training algorithm

Parameters
nClassesNumber of classes
solverOptimization solver

Variant 3

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

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

Invokes computations

def getInput (   self)

Get input objects for the logistic regression training algorithm

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

Returns the method of the algorithm

Returns
Method of the algorithm
def getResult (   self)

Returns the structure that contains results of logistic regression training

Returns
Structure that contains results of logistic regression training
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
def resetResult (   self)

Resets the training results of the algorithm

Member Data Documentation

input = ...
static

Input data structure


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

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