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Please use this identifier to cite or link to this item:

http://hdl.handle.net/20.500.12358/24902
TitleAvoiding objects with few neighbors in the K-Means process and adding ROCK Links to its distance
Untitled
Abstract

K-means is considered as one of the most common and powerful algorithms in data clustering, in this paper we're going to present new techniques to solve two problems in the K-means traditional clustering algorithm, the 1st problem is its sensitivity for outliers, in this part we are going to depend on a function that will help us to decide if this object is an outlier or not, if it was an outlier it will be expelled from our calculations, that will help the K-means to make good results even if we added more outlier points; in the second part we are going to make K-means depend on Rock links in addition to its traditional distance, Rock links takes into account the number of common neighbors between two objects, that will make the K-means able to detect shapes that can't be detected by the traditional K-means.

Authors
Alnabriss, Hadi A
Ashour, Wesam M.
TypeJournal Article
Date2011
Subjects
rock links
optimizing k-means distance measurement
general terms data clustering algorithms
k-means
rock
centroids' initialization robust k-means
optimized k-means
initializing k-means
electing centroids
Published inInternational Journal of Computer Applications
SeriesVolume: 28, Number: 10
PublisherInternational Journal of Computer Applications, 244 5 th Avenue,# 1526, New York, NY 10001, USA India
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  • Staff Publications- Faculty of Engineering [906]
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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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