An improved algorithm for mining non-redundant interacting feature subsets

  • Chaofeng Sha*
  • , Jian Gong
  • , Aoying Zhou
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The application of feature subsets with high order correlation in classification has demonstrates its power in a recent study, where non-redundant interacting feature subsets (NIFS) is defined based on multi-information. In this paper, we re-examine the problem of finding NIFSs. We further improve the upper bounds and lower bounds on the correlations, which can be used to significantly prune the search space. The experiments on real datasets demonstrate the efficiency and effectiveness of our approach.

Original languageEnglish
Title of host publicationAdvances in Data and Web Management - Joint International Conferences, APWeb/WAIM 2009, Proceedings
PublisherSpringer Verlag
Pages357-368
Number of pages12
ISBN (Print)9783642006715
DOIs
StatePublished - 2009
EventJoint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009 - Suzhou, China
Duration: 2 Apr 20094 Apr 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5446
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceJoint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009
Country/TerritoryChina
CitySuzhou
Period2/04/094/04/09

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