python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy Class Reference

The class implements heuristics for testing if the learn process should be finished before learner is overfitted. More...

Inheritance diagram for python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy:

Public Member Functions
	__init__ (self)
	Contructor.
	fromJson (cls, jsonObject)
	getAccuracyLimit (self)
	Returns the accuracy on validation data, that have to be achieved.
	getAdaptiveIterationLimit (self)
	Returns the maximal number of refinement iterations.
	getGridSizeLimit (self)
	Returns the maximal grid size.
	hasGridSizeChanged (self, sampler)
	hasLimitReached (self, sampler)
	isTrainingComplete (self, sampler)
	Checks if learning process have to be stopped.
	setAccuracyLimit (self, limit)
	Setter for accuracy limit.
	setAdaptiveIterationLimit (self, limit)
	setGridSizeLimit (self, limit)
	Setter for maximal grid size.
	toString (self)
	Returns a string that represents the object.

Detailed Description

The class implements heuristics for testing if the learn process should be finished before learner is overfitted.

The test is made by calling method isTrainingComplete(learner) of the class, which returns True if training process should be finished.

Constructor & Destructor Documentation

__init__()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__init__

(

self

)

Contructor.

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__accuracyLimit, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__accuracyLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__adaptiveIterationLimit, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__adaptiveIterationLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__gridSizeLimit, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__gridSizeLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__oldGridSize, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__oldGridSize.

Member Function Documentation

fromJson()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.fromJson	(		cls,
			jsonObject
	)

Referenced by python.learner.Learner.Learner.setMemento(), python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.setMemento(), python.uq.learner.Learner.Learner.setMemento(), python.uq.sampler.asgc.ASGCSampler.ASGCSampler.setMemento(), and python.uq.uq_setting.UQSetting.UQSetting.setMemento().

getAccuracyLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.getAccuracyLimit

(

self

)

Returns the accuracy on validation data, that have to be achieved.

Returns

: accuracy on validation data, that have to be achieved

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__accuracyLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__accuracyLimit.

getAdaptiveIterationLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.getAdaptiveIterationLimit

(

self

)

Returns the maximal number of refinement iterations.

Returns

: the maximal number of refinement iterations

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__adaptiveIterationLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__adaptiveIterationLimit.

getGridSizeLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.getGridSizeLimit

(

self

)

Returns the maximal grid size.

Returns

: maximal grid size

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__gridSizeLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__gridSizeLimit.

Referenced by python.learner.TrainingStopPolicy.TrainingStopPolicy.hasLimitReached(), and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.hasLimitReached().

hasGridSizeChanged()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.hasGridSizeChanged	(		self,
			sampler
	)

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__oldGridSize, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__oldGridSize.

Referenced by python.learner.TrainingStopPolicy.TrainingStopPolicy.isTrainingComplete(), and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.isTrainingComplete().

hasLimitReached()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.hasLimitReached	(		self,
			sampler
	)

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__adaptiveIterationLimit, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__adaptiveIterationLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.getGridSizeLimit(), and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.getGridSizeLimit().

Referenced by python.learner.TrainingStopPolicy.TrainingStopPolicy.isTrainingComplete(), and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.isTrainingComplete().

isTrainingComplete()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.isTrainingComplete	(		self,
			sampler
	)

Checks if learning process have to be stopped.

Parameters

sampler

Learner object

Returns

: boolean value, true if learning has to stop, false otherwise

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__oldGridSize, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__oldGridSize, python.learner.TrainingStopPolicy.TrainingStopPolicy.hasGridSizeChanged(), python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.hasGridSizeChanged(), python.learner.TrainingStopPolicy.TrainingStopPolicy.hasLimitReached(), and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.hasLimitReached().

setAccuracyLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.setAccuracyLimit	(		self,
			limit
	)

Setter for accuracy limit.

Parameters

limit

double accuracy on validation data, that have to be achieved

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__accuracyLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__accuracyLimit.

setAdaptiveIterationLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.setAdaptiveIterationLimit	(		self,
			limit
	)

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__adaptiveIterationLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__adaptiveIterationLimit.

setGridSizeLimit()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.setGridSizeLimit	(		self,
			limit
	)

Setter for maximal grid size.

Parameters

limit

integer maximal grid size

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__gridSizeLimit, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__gridSizeLimit.

toString()

python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.toString

(

self

)

Returns a string that represents the object.

Returns

A string that represents the object. )

Referenced by python.controller.LearnerEventController.LearnerEventController.__repr__(), python.controller.SolverEventController.SolverEventController.__repr__(), python.learner.Learner.Learner.createMemento(), python.uq.learner.Learner.Learner.createMemento(), and python.learner.formatter.GridFormatter.GridFormatter.serialize().

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

• datadriven/python/uq/sampler/asgc/ASGCSamplerStopPolicy.py