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java.lang.Objectedu.udo.cs.yale.operator.Operator
edu.udo.cs.yale.operator.OperatorChain
edu.udo.cs.yale.operator.features.FeatureOperator
edu.udo.cs.yale.operator.features.weighting.FeatureWeighting
edu.udo.cs.yale.operator.features.weighting.ForwardWeighting
public class ForwardWeighting
This operator performs the weighting under the naive assumption that the features are independent from each other. Each attribute is weighted with a linear search. This approach may deliver good results after short time if the features indeed are not highly correlated.
| Constructor Summary | |
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ForwardWeighting(OperatorDescription description)
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| Method Summary | |
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Population |
createInitialPopulation(ExampleSet es)
Create an initial population. |
PopulationOperator |
getWeightingOperator(java.lang.String parameter)
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| Methods inherited from class edu.udo.cs.yale.operator.features.weighting.FeatureWeighting |
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apply, getParameterTypes, getPostEvaluationPopulationOperators, getPreEvaluationPopulationOperators, solutionGoodEnough |
| Methods inherited from class edu.udo.cs.yale.operator.features.FeatureOperator |
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evaluate, evaluate, getCheckForMaximum, getInnerOperatorCondition, getInputClasses, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getNumberOfSteps, getOutputClasses, getRandom, setCheckForMaximum |
| Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
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public ForwardWeighting(OperatorDescription description)
| Method Detail |
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public PopulationOperator getWeightingOperator(java.lang.String parameter)
getWeightingOperator in class FeatureWeightingpublic Population createInitialPopulation(ExampleSet es)
FeatureOperator
createInitialPopulation in class FeatureOperator
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