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

Public Member Functions | List of all members
Parameter Class Reference

Parameter for the Stochastic gradient descent algorithm More...

Public Member Functions

def __init__
 
def check
 
- Public Member Functions inherited from BaseParameter
def __init__
 
def check
 
- Public Member Functions inherited from Parameter
def __init__
 
def check
 
- Public Member Functions inherited from Parameter
def __init__
 
def check
 

Additional Inherited Members

- Static Public Attributes inherited from BaseParameter
 batchIndices = ...
 
 learningRateSequence = ...
 
 seed = ...
 
- Static Public Attributes inherited from Parameter
 function = ...
 
 nIterations = ...
 
 accuracyThreshold = ...
 
 optionalResultRequired = ...
 

Detailed Description

Aliases
  • Parameter_DefaultDense is an alias of Parameter(method=daal.algorithms.optimization_solver.sgd.defaultDense)
  • Parameter_MiniBatch is an alias of Parameter(method=daal.algorithms.optimization_solver.sgd.miniBatch)
  • Parameter_Momentum is an alias of Parameter(method=daal.algorithms.optimization_solver.sgd.momentum)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Variant 2
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Variant 3
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Variant 4
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Variant 5
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Variant 6
Parameters
functionObjective function represented as sum of functions
nIterationsMaximal number of iterations of the algorithm
accuracyThresholdAccuracy of the algorithm. The algorithm terminates when this accuracy is achieved
batchIndicesNumeric table that represents 32 bit integer indices of terms in the objective function. If no indices are provided, the implementation will generate random indices.
learningRateSequenceNumeric table that contains values of the learning rate sequence
seedSeed for random generation of 32 bit integer indices of terms in the objective function.
Deprecated:
This item will be removed in a future release. Use engine instead.

Member Function Documentation

def check (   self)

Checks the correctness of the parameter

Returns
Status of computations

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

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