weka.associations

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## Package weka.associations

Interface Summary
Associator |
CARuleMiner | Interface for learning class association rules.

Class Summary
AbstractAssociator | Abstract scheme for learning associations.
Apriori | Class implementing an Apriori-type algorithm.
AprioriItemSet | Class for storing a set of items.
AssociatorEvaluation | Class for evaluating Associaters.
CaRuleGeneration | Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.
CheckAssociator | Class for examining the capabilities and finding problems with associators.
FilteredAssociator | Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
GeneralizedSequentialPatterns | Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set. The attribute identifying the distinct data sequences contained in the set can be determined by the respective option.
HotSpot | HotSpot learns a set of rules (displayed in a tree-like structure) that maximize/minimize a target variable/value of interest.
ItemSet | Class for storing a set of items.
LabeledItemSet | Class for storing a set of items together with a class label.
PredictiveApriori | Class implementing the predictive apriori algorithm to mine association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence.
PriorEstimation | Class implementing the prior estimattion of the predictive apriori algorithm for mining association rules.
RuleGeneration | Class implementing the rule generation procedure of the predictive apriori algorithm.
RuleItem | Class for storing an (class) association rule.
SingleAssociatorEnhancer | Abstract utility class for handling settings common to meta associators that use a single base associator.
Tertius | Finds rules according to confirmation measure (Tertius-type algorithm). For more information see: P.

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