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http://hdl.handle.net/20.500.12358/25191
TitleA comparative study of outlier mining and class outlier mining
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Abstract

Outliers can significantly affect data mining performance. Outlier mining is an important issue in knowledge discovery and data mining and has attracted increasing interests in recent years. Class outlier is promising research direction. Few researches have been done in this direction. The paper theme has two main goals: the first one is to show the significance of Class Outlier Mining by discussing a comparative study between a Class Outlier detection method called Class Outlier Distance Based (CODB) and a conventional Outlier detection method. The second goal is to introduce

Authors
Saad, Motaz K
Hewahi, Nabil M
TypeJournal Article
Date2009
Subjects
outlier
class outlier
distance based approach
Published inComputer Science Letters
SeriesVolume: 1, Number: 1
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  • Staff Publications- Faculty of Information Technology [192]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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