Package edu.udo.cs.yale.operator.features.weighting

Operators to weight features or determine feature relevance.

See:
Description

Class Summary

AttributeWeightsCreator	This operator creates a new attribute weights IOObject from a given example set.
BackwardWeighting	Uses the backward selection idea for the weighting of features.
ComponentWeights	For models creating components like PCA, GHA and FastICA you can create the AttributeWeights for a component.
CorpusBasedFeatureWeighting	This operator uses a corpus of examples to characterize a single class by setting feature weights.
CorrelationMatrixOperator	This operator calculates the correlation matrix between all attributes of the input example set.
EvolutionaryWeighting	This operator performs the weighting of features with an evolutionary strategies approach.
FeatureWeighting	This operator performs the weighting under the naive assumption that the features are independent from each other.
ForwardWeighting	This operator performs the weighting under the naive assumption that the features are independent from each other.
GenericWekaAttributeWeighting	Performs the AttributeEvaluator of Weka with the same name to determine a sort of attribute relevance.
InteractiveAttributeWeighting	This operator shows a window with the currently used attribute weights and allows users to change the weight interactively.
PSOWeighting	This operator performs the weighting of features with a particle swarm approach.
PSOWeighting.PSOWeightingOptimization	The optimization class.
SimpleWeighting	This PopulationOperator realises a simple weighting, i.e. creates a list of clones of each individual and weights one attribute in each of the clones with some different weights.
StandardDeviationWeighting	Creates a plot of the standard deviations of all attributes.
VarianceAdaption	Implements the 1/5-Rule for dynamic parameter adaption of the variance of a WeightingMutation.
WeightingCrossover	Crossover operator for the used weights of example sets.
WeightingMutation	Changes the weight for all attributes by multiplying them with a gaussian distribution.

Package edu.udo.cs.yale.operator.features.weighting Description

Operators to weight features or determine feature relevance.