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

Meta learning schemes which uses other learning operators to increase the performance.

See:
Description

Class Summary

AbstractMetaLearner	A MetaLearner is an operator that encapsulates one or more learning steps to build its model.
AdaBoost	This AdaBoost implementation can be used with all learners available in YALE, not only the ones which originally are part of the Weka package.
AdaBoostModel	A model for the Yale AdaBoost implementation.
AdaBoostPerformanceMeasures	Helper class for the internal AdaBoost implementation.
Bagging	This Bagging implementation can be used with all learners available in YALE, not only the ones which originally are part of the Weka package.
BaggingModel	The model for the internal Bagging implementation.
BayBoostBaseModelInfo	Stores a base model together with its contingency matrix, which offerers a more convenient access in the context of ensemble classification.
BayBoostModel	A model for the Bayesian Boosting algorithm by Martin Scholz.
BayBoostStream	Assumptions: target label is always boolean goal is to fit a crisp ensemble classifier (use_distribution always off) base classifier weights are always adapted by a single row from first to last no internal bootstrapping
BayesianBoosting	This operator trains an ensemble of classifiers for boolean target attributes.
ClassificationByRegression	For a classified dataset (with possibly more than two classes) builds a classifier using a regression method which is specified by the inner operator.
ContingencyMatrix	This class computes the contingency matrix of classifiers, supports weighted example sets and contains some convenience methods to query for some evaluation metrics that can directly be computed from this matrix.
MultiModel	MultiModels are used for multi class learning tasks.
MultiModelByRegression	MultiModels are used for multi class learning tasks.
SDEnsemble	A subgroup discovery model.
SDReweightMeasures	A set of weighted performance measures used for subgroup discovery.
SDRulesetInduction	Subgroup discovery learner.
TransformedRegression	This meta learner applies a transformation on the label before the inner regression learner is applied.
TransformedRegressionModel	Model for TransformedRegression.
WeightedPerformanceMeasures	This private class cares about weighted performance measures as used by the BayesianBoosting algorithm and the similarly working ModelBasedSampling operator.

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

Meta learning schemes which uses other learning operators to increase the performance.