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

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

Provides methods for linear regression model-based training in the online processing mode. More...

Public Member Functions

def __init__
 
def getInput
 
def getMethod
 
def getPartialResult
 
def getResult
 
def clone
 
def compute
 
def finalizeCompute
 
- Public Member Functions inherited from Online
def getPartialResult
 
def getResult
 
def compute
 
- Public Member Functions inherited from Online
def getInput
 
def setPartialResult
 
def setResult
 
def getPartialResult
 
def getResult
 
def compute
 

Static Public Attributes

 input = ...
 
 parameter = ...
 

Detailed Description

Parameters
fptypeData type to use in intermediate computations for linear regression model-based training , double or float
methodLinear regression training method, Method
Enumerations
  • Method Computation methods
References
Aliases
  • Online_Float64QrDense is an alias of Online(fptype=float64, method=daal.algorithms.linear_regression.training.qrDense)
  • Online_Float64NormEqDense is an alias of Online(fptype=float64, method=daal.algorithms.linear_regression.training.normEqDense)
  • Online_Float32QrDense is an alias of Online(fptype=float32, method=daal.algorithms.linear_regression.training.qrDense)
  • Online_Float32NormEqDense is an alias of Online(fptype=float32, method=daal.algorithms.linear_regression.training.normEqDense)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1
Default constructor

Variant 2

Constructs a linear regression training algorithm by copying input objects and parameters of another linear regression training algorithm in the online processing mode

Parameters
otherAlgorithm to use as the source to initialize the input objects and parameters of the algorithm

Member Function Documentation

def clone (   self)

Returns a pointer to a newly allocated linear regression training algorithm with a copy of the input objects and parameters of this linear regression training algorithm in the online processing mode

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 getInput (   self)

getInput(Online self) -> Input

def getMethod (   self)

Returns the method of the algorithm

Returns
Method of the algorithm
def getPartialResult (   self)

Returns the structure that contains a partial result of linear regression model-based training

Returns
Structure that contains a partial result of linear regression model-based training
def getResult (   self)

Returns the structure that contains the result of linear regression model-based training

Returns
Structure that contains the result of linear regression model-based training

Member Data Documentation

input = ...
static

Input data structure

parameter = ...
static

Training parameters


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

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