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Avoiding Objects with few Neighbors in the K-Means Process and Adding ROCK Links to Its Distance

by Hadi A. Alnabriss, Wesam Ashour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 10
Year of Publication: 2011
Authors: Hadi A. Alnabriss, Wesam Ashour
10.5120/3421-4040

Hadi A. Alnabriss, Wesam Ashour . Avoiding Objects with few Neighbors in the K-Means Process and Adding ROCK Links to Its Distance. International Journal of Computer Applications. 28, 10 ( August 2011), 12-17. DOI=10.5120/3421-4040

@article{ 10.5120/3421-4040,
author = { Hadi A. Alnabriss, Wesam Ashour },
title = { Avoiding Objects with few Neighbors in the K-Means Process and Adding ROCK Links to Its Distance },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 10 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number10/3421-4040/ },
doi = { 10.5120/3421-4040 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:14:25.398875+05:30
%A Hadi A. Alnabriss
%A Wesam Ashour
%T Avoiding Objects with few Neighbors in the K-Means Process and Adding ROCK Links to Its Distance
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 10
%P 12-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
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.

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Index Terms

Computer Science
Information Sciences

Keywords

Robust K-means Rock links Initializing K-means electing centroids Optimizing K-means distance measurement

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