Package org.knime.base.node.mine.subgroupminer.apriori

This package contains two algorithm implementations for the SubgroupMinerNode.

See:
          Description

Interface Summary
AprioriAlgorithm This is an interface to hide the different implementations of the apriori algorithm to the Nodes.
 

Class Summary
AprioriAlgorithmFactory To hide the different implementations of the apriori algorithm to the NodeModel, the NodeDialog simply displays the registered AlgorithmDataStructure's and the NodeModel passes it to this factory.
ArrayApriori The array apriori uses the ArrayPrefixTreeNode data structure to find frequent itemsets.
ArrayPrefixTreeNode An ArrayPrefixTreeNode contains an array containing the counter for the items, where the array position serves as the item identifier.
TIDApriori The TIDApriori algorithm is actually an Eclat implementation, since it realizes a depth first search.
TIDItem The TIDItem consists of an id and a BitSet, where each bit corresponds to a transaction id and is set, if this item is present in the transaction.
TIDItemSet The TIDItemSet contains of some TIDItems and a BitSet with their common transaction ids.
TIDPrefixTreeNode An TIDPrefixTreeNode consists of a TIDItemset, the items in the node, and a list of children of this node.
 

Enum Summary
AprioriAlgorithmFactory.AlgorithmDataStructure Register here possible implementations of the apriori algorithm to be provided by the subgroup miner node (SubgroupMinerModel).
 

Package org.knime.base.node.mine.subgroupminer.apriori Description

This package contains two algorithm implementations for the SubgroupMinerNode. The ArrayApriori algorithm realizes the apriori algorithm with the help of a prefix tree, where the nodes are arrays, each containing a counter at the corresponding position. The TIDAprioriAlgorithm is indeed an Eclat implementation, since it realizes the subgroup mining in a depth-first-search manner by combining the transaction ids of each item with the other ones.



Copyright, 2003 - 2010. All rights reserved.
University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
You may not modify, publish, transmit, transfer or sell, reproduce, create derivative works from, distribute, perform, display, or in any way exploit any of the content, in whole or in part, except as otherwise expressly permitted in writing by the copyright owner or as specified in the license file distributed with this product.