程序包 weka.associations


package weka.associations
  • 说明
    Abstract scheme for learning associations.
    Class implementing an Apriori-type algorithm.
    Class for storing a set of items.
     
    Class for evaluating Associaters.
    Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.
    Interface for learning class association rules.
    Class for examining the capabilities and finding problems with associators.
    Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
    Class implementing the FP-growth algorithm for finding large item sets without candidate generation.
     
    Enum for holding different metric types
    Inner class that handles a single binary item
    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.
    Class for storing a set of items.
    Class for storing a set of items together with a class label.
    Messages.
    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.
    Class implementing the prior estimattion of the predictive apriori algorithm for mining association rules.
    Class implementing the rule generation procedure of the predictive apriori algorithm.
    Class for storing an (class) association rule.
    Abstract utility class for handling settings common to meta associators that use a single base associator.
    Finds rules according to confirmation measure (Tertius-type algorithm).

    For more information see:

    P.