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RK-Means Clustering: K-Means with Reliability

Authors:

Toshikazu WadaAuthors Info & Claims

IEICE - Transactions on Information and Systems, Volume E91-D, Issue 1

Pages 96 - 104

https://doi.org/10.1093/ietisy/e91-d.1.96

Published: 01 January 2008 Publication History

Abstract

This paper presents an RK-means clustering algorithm which is developed for reliable data grouping by introducing a new reliability evaluation to the K-means clustering algorithm. The conventional K-means clustering algorithm has two shortfalls: 1) the clustering result will become unreliable if the assumed number of the clusters is incorrect; 2) during the update of a cluster center, all the data points belong to that cluster are used equally without considering how distant they are to the cluster center. In this paper, we introduce a new reliability evaluation to K-means clustering algorithm by considering the triangular relationship among each data point and its two nearest cluster centers. We applied the proposed algorithm to track objects in video sequence and confirmed its effectiveness and advantages.

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Cited By

Shu ZCarrasco González RGarcía-Miguel JSánchez-Montañés M(2023)Clustering using ordered weighted averaging operator and 2-tuple linguistic model for hotel segmentationExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.118922213:PAOnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.118922
Shu ZCarrasco González RGarcía-Miguel JSánchez-Montañés M(2023)A Model Integrating the 2-Tuple Linguistic Model and the CRITIC-AHP Method for Hotel ClassificationSN Computer Science10.1007/s42979-023-02344-55:1Online publication date: 15-Nov-2023
https://dl.acm.org/doi/10.1007/s42979-023-02344-5

RK-Means Clustering: K-Means with Reliability
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. Information systems applications
    1. Data mining

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cover image IEICE - Transactions on Information and Systems

IEICE - Transactions on Information and Systems Volume E91-D, Issue 1

January 2008

157 pages

ISSN:0916-8532

EISSN:1745-1361

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Copyright © Copyright © 2008 The Institute of Electronics, Information and Communication Engineers.

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Oxford University Press, Inc.

United States

Publication History

Published: 01 January 2008

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Cited By

Shu ZCarrasco González RGarcía-Miguel JSánchez-Montañés M(2023)Clustering using ordered weighted averaging operator and 2-tuple linguistic model for hotel segmentationExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.118922213:PAOnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.118922
Shu ZCarrasco González RGarcía-Miguel JSánchez-Montañés M(2023)A Model Integrating the 2-Tuple Linguistic Model and the CRITIC-AHP Method for Hotel ClassificationSN Computer Science10.1007/s42979-023-02344-55:1Online publication date: 15-Nov-2023
https://dl.acm.org/doi/10.1007/s42979-023-02344-5

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