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

Inheritance diagram for python.learner.TrainingStopPolicy.TrainingStopPolicy:

Public Member Functions
	__init__ (self)
	Contructor.

	fromJson (cls, jsonObject)
	Restores the TrainingStopPolicy object from the json object with attributes.

	getAccuracyLimit (self)
	Returns the accuracy on validation data, that have to be achieved.

	getAdaptiveIterationLimit (self)
	Returns the maximal number of refinement iterations.

	getEpochsLimit (self)
	Returns the maximal number of iterations, during which accuracy can decreases.

	getGridSize (self, learner)

	getGridSizeLimit (self)
	Returns the maximal grid size.

	getMSELimit (self)
	Returns MSE on validation data, that have to be achieved.

	hasGridSizeChanged (self, learner)

	hasLimitReached (self, learner)

	isTrainingComplete (self, learner)
	Checks if learning process have to be stopped.

	setAccuracyLimit (self, limit)
	Setter for accuracy limit.

	setAdaptiveIterationLimit (self, limit)

	setEpochsLimit (self, limit)
	Setter for epochs limit.

	setGridSizeLimit (self, limit)
	Setter for maximal grid size.

	setMSELimit (self, limit)
	Setter for MSE limit.

	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.learner.TrainingStopPolicy.TrainingStopPolicy.__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.__epochsLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__gridSizeLimit, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__gridSizeLimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__MSELimit, python.learner.TrainingStopPolicy.TrainingStopPolicy.__oldGridSize, and python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__oldGridSize.

Member Function Documentation

◆ fromJson()

python.learner.TrainingStopPolicy.TrainingStopPolicy.fromJson	(	cls,
		jsonObject
	)

Restores the TrainingStopPolicy object from the json object with attributes.

Parameters

cls	python keyword (do not specify)
jsonObject	A json object.

Returns: The restored TrainingStopPolicy object.

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.learner.TrainingStopPolicy.TrainingStopPolicy.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.learner.TrainingStopPolicy.TrainingStopPolicy.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.

◆ getEpochsLimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.getEpochsLimit ( self )

Returns the maximal number of iterations, during which accuracy can decreases.

Returns: : the maximal number of iterations, during which accuracy can decreases

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__epochsLimit.

◆ getGridSize()

python.learner.TrainingStopPolicy.TrainingStopPolicy.getGridSize	(	self,
		learner
	)

Referenced by python.learner.TrainingStopPolicy.TrainingStopPolicy.hasGridSizeChanged(), and python.learner.TrainingStopPolicy.TrainingStopPolicy.isTrainingComplete().

◆ getGridSizeLimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.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().

◆ getMSELimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.getMSELimit ( self )

Returns MSE on validation data, that have to be achieved.

Returns: : MSE on validation data, that have to be achieved

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__MSELimit.

Referenced by python.learner.TrainingStopPolicy.TrainingStopPolicy.hasLimitReached().

◆ hasGridSizeChanged()

python.learner.TrainingStopPolicy.TrainingStopPolicy.hasGridSizeChanged	(	self,
		learner
	)

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__oldGridSize, python.uq.sampler.asgc.ASGCSamplerStopPolicy.ASGCSamplerStopPolicy.__oldGridSize, sgpp::datadriven::DBMatOffline.getGridSize(), sgpp::datadriven::ClassificationLearner.getGridSize(), sgpp::datadriven::RegressionLearner.getGridSize(), and python.learner.TrainingStopPolicy.TrainingStopPolicy.getGridSize().

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

◆ hasLimitReached()

python.learner.TrainingStopPolicy.TrainingStopPolicy.hasLimitReached	(	self,
		learner
	)

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

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

◆ isTrainingComplete()

python.learner.TrainingStopPolicy.TrainingStopPolicy.isTrainingComplete	(	self,
		learner
	)

Checks if learning process have to be stopped.

Parameters

learner 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, sgpp::datadriven::DBMatOffline.getGridSize(), sgpp::datadriven::ClassificationLearner.getGridSize(), sgpp::datadriven::RegressionLearner.getGridSize(), python.learner.TrainingStopPolicy.TrainingStopPolicy.getGridSize(), 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.learner.TrainingStopPolicy.TrainingStopPolicy.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.learner.TrainingStopPolicy.TrainingStopPolicy.setAdaptiveIterationLimit	(	self,
		limit
	)

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

◆ setEpochsLimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.setEpochsLimit	(	self,
		limit
	)

Setter for epochs limit.

Parameters

limit integer Maximal number of iterations, during which accuracy can decreases

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__epochsLimit.

◆ setGridSizeLimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.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.

◆ setMSELimit()

python.learner.TrainingStopPolicy.TrainingStopPolicy.setMSELimit	(	self,
		limit
	)

Setter for MSE limit.

Parameters

limit double minimal MSE on validation data, that have to be achieved

References python.learner.TrainingStopPolicy.TrainingStopPolicy.__MSELimit.

◆ toString()

python.learner.TrainingStopPolicy.TrainingStopPolicy.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().

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

datadriven/python/learner/TrainingStopPolicy.py

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ __init__()

Member Function Documentation

◆ fromJson()

◆ getAccuracyLimit()

◆ getAdaptiveIterationLimit()

◆ getEpochsLimit()

◆ getGridSize()

◆ getGridSizeLimit()

◆ getMSELimit()

◆ hasGridSizeChanged()

◆ hasLimitReached()

◆ isTrainingComplete()

◆ setAccuracyLimit()

◆ setAdaptiveIterationLimit()

◆ setEpochsLimit()

◆ setGridSizeLimit()

◆ setMSELimit()

◆ toString()

◆ init()