Package weka.associations

Interface Summary
CARuleMiner Interface for learning class association rules.
 

Class Summary
Apriori Class implementing an Apriori-type algorithm.
AprioriItemSet Class for storing a set of items.
Associator Abstract scheme for learning associations.
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.
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.