Package edu.udo.cs.yale.operator.meta

Provides YALE operators for experiment iteration, meta operators, and optimization.

See:
Description

Class Summary

AverageBuilder	Collects all average vectors (e.g.
ESParameterOptimization	Evolutionary Strategy approach for an evolutionary parameter optimization.
EvolutionaryParameterOptimizationOperator	This operator finds the optimal values for a set of parameters using an evolutionary strategies approach which is often more appropriate than a grid search or a greedy search like the quadratic programming approach and leads to better results.
ExampleSetIterator	For each example set the ExampleSetIterator finds in its input, the inner operators are applied as if it was an OperatorChain.
ExperimentEmbeddingOperator	This operator can be used to embed a complete experiment into the current experiment.
GridSearchParameterOptimizationOperator	This operator finds the optimal values for a set of parameters using a grid search.
IteratingOperatorChain	Performs its inner operators for the defined number of times.
IterativeWeightOptimization	Performs an iterative feature selection guided by the AttributeWeights.
MartinsIterationOperator	Obsolete.
MultipleLabelIterator	Performs the inner operator for all label attributes, i.e. special attributes whose name starts with "label".
OperatorEnabler	This operator can be used to enable and disable other operators.
ParameterCloner	Sets a list of parameters using existing parameter values.
ParameterIteration	In contrast to the ParameterOptimizationOperator operator this operators simply uses the defined parameters and perform the inner operators for all possible combinations.
ParameterOptimizationOperator	This operator provides basic functions for all other parameter optimization operators.
ParameterSet	A set of parameters generated by a ParameterOptimizationOperator.
ParameterSet.ParameterValue	The best value of a parameter of an operator.
ParameterSetter	Sets a set of parameters.
QuadraticParameterOptimizationOperator	This operator finds the optimal values for a set of parameters using a quadratic interaction model.
RandomOptimizationChain	This operator iterates several times through the inner operators and in each cycle evaluates a performance measure.
RepeatUntilOperatorChain	Performs its inner operators until all given criteria is met or a timeout occurs.
WeightOptimization	Performs a feature selection guided by the AttributeWeights.
XVPrediction	Operator chain that splits an ExampleSet into a training and test sets similar to XValidation, but returns the test set predictions instead of a performance vector.

Package edu.udo.cs.yale.operator.meta Description

Provides YALE operators for experiment iteration, meta operators, and optimization.