15-12-2025
جامعة الملك عبدالعزيز
KING ABDULAZIZ UNIVERSITY
Faculty of Computing and Information Technology in Rabigh
Document Details
Document Type
:
Article In Journal
Document Title
:
Cluster center initialization algorithm for K-modes clustering
خوارزمية التهيئة لمركز الكتلة لمجموعات تقسيم K-modes
Subject
:
Computer Science
Document Language
:
English
Abstract
:
Partitional clustering of categorical data is normally performed by using K-modes clustering algorithm, which works well for large datasets. Even though the design and implementation of K-modes algorithm is simple and efficient, it has the pitfall of randomly choosing the initial cluster centers for invoking every new execution that may lead to non-repeatable clustering results. This paper addresses the randomized center initialization problem of K-modes algorithm by proposing a cluster center initialization algorithm. The proposed algorithm performs multiple clustering of the data based on attribute values in different attributes and yields deterministic modes that are to be used as initial cluster centers. In the paper, we propose a new method for selecting the most relevant attributes, namely Prominent attributes, compare it with another existing method to find Significant attributes for unsupervised learning, and perform multiple clustering of data to find initial cluster centers. The proposed algorithm ensures fixed initial cluster centers and thus repeatable clustering results. The worst-case time complexity of the proposed algorithm is log-linear to the number of data objects. We evaluate the proposed algorithm on several categorical datasets and compared it against random initialization and two other initialization methods, and show that the proposed method performs better in terms of accuracy and time complexity. The initial cluster centers computed by the proposed approach are close to the actual cluster centers of the different data we tested, which leads to faster convergence of K-modes clustering algorithm in conjunction to better clustering results
ISSN
:
0957-4174
Journal Name
:
Expert Systems with Applications
Volume
:
40
Issue Number
:
18
Publishing Year
:
1433 AH
2012 AD
Article Type
:
Article
Added Date
:
Wednesday, November 6, 2013
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
أمير احمد
Ahmad, Amir
Researcher
Doctorate
amirahmad01@gmail.com
Shehroz Khan
Khan, Shehroz
Researcher
Files
File Name
Type
Description
36341.pdf
pdf
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