Data squashing for speeding up boosting-based outlier detection

Shutaro Inatani, Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


In this paper, we apply data squashing to speed up outlier detection based on boosting. One person's noise is another person's signal. Outlier detection is gaining increasing attention in data mining. In order to improve computational time for AdaBoost-based outlier detection, we beforehand compress a given data set based on a simplified method of BIRCH. Effectiveness of our approach in terms of detection accuracy and computational time is investigated by experiments with two real-world data sets of drug stores in Japan and an artificial data set of unlawful access to a computer network.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - 13th International Symposium, ISMIS 2002, Proceedings
EditorsMohand-Said Hacid, Zbigniew W. Ras, Djamel A. Zighed, Yves Kodratoff
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3540437851, 9783540437857
Publication statusPublished - 2002
Externally publishedYes
Event13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002 - Lyon, France
Duration: Jun 27 2002Jun 29 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2366 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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