Title: Multi-class correlated pattern mining
Authors: Nijssen, Siegfried ×
Kok, JN #
Issue Date: 2006
Publisher: Springer-verlag berlin
Series Title: Knowledge discovery in inductive databases vol:3933 pages:165-187
Abstract: To mine databases in which examples are tagged with class labels, the minimum correlation constraint has been studied as an alternative to the minimum frequency constraint. We reformulate previous approaches and show that a minimum correlation constraint can be transformed into a disjunction of minimum frequency constraints. We prove that this observation extends to the multi-class chi(2) correlation measure, and thus obtain an efficient new O(n) prune test. We illustrate how the relation between correlation measures and minimum support thresholds allows for the reuse of previously discovered pattern sets, thus avoiding unneccessary database evaluations. We conclude with experimental results to assess the effectivity of algorithms based on our observations.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Non-KU Leuven Association publications
× corresponding author
# (joint) last author

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