Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

List of all members
TrainingDistributedStep2Master Class Reference

Runs linear regression model-based training in the second step of the distributed processing mode. More...

Class Constructor

◆ TrainingDistributedStep2Master() [1/2]

Constructs a linear regression training algorithm by copying input objects and parameters of another linear regression training algorithm

Parameters
contextContext to manage linear regression model-based training
otherAlgorithm to use as the source to initialize the input objects and parameters of the algorithm

◆ TrainingDistributedStep2Master() [2/2]

TrainingDistributedStep2Master ( DaalContext  context,
Class<? extends Number >  cls,
TrainingMethod  method 
)

Constructs the linear regression training algorithm in the second step of the distributed processing mode

Parameters
contextContext to manage linear regression model-based training
clsData type to use in intermediate computations of linear regression, Double.class or Float.class
methodAlgorithm computation method, TrainingMethod

Detailed Description

References

Member Function Documentation

◆ clone()

Returns a newly allocated linear regression training algorithm with a copy of the input objects and parameters of this linear regression training algorithm in the second step of the distributed processing mode

Parameters
contextContext to manage linear regression model-based training
Returns
Newly allocated algorithm

◆ compute()

PartialResult compute ( )

Computes a partial result of linear regression model-based training in the second step of the distributed processing mode

Returns
Partial result of linear regression model-based training in the second step of the distributed processing mode

◆ finalizeCompute()

TrainingResult finalizeCompute ( )

Computes the result of linear regression model-based training in the second step of the distributed processing mode

Returns
Result of linear regression model-based training in the second step of the distributed processing mode

Member Data Documentation

◆ input

Input data

◆ method

Training method for the algorithm

◆ parameter

Parameter parameter

Parameters of the algorithm


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

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