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K-Means Clustering for Problems with Periodic Attributes

SYSNO ASEP	0328432
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	K-Means Clustering for Problems with Periodic Attributes
Title	Shlukovací algoritmus K-Means v problémech s periodickými atributy
Author(s)	Vejmelka, Martin (UIVT-O)_{SAI, RID, ORCID} Musílek, P. (CA) Paluš, Milan (UIVT-O)_{RID, SAI, ORCID} Pelikán, Emil (UIVT-O)_{SAI, RID}
Source Title	International Journal of Pattern Recognition and Artificial Intelligence - ISSN 0218-0014 Roč. 23, č. 4 (2009), s. 721-743
Number of pages	23 s.
Language	eng - English
Country	SG - Singapore
Keywords	clustering algorithms ; similarity measures ; K-means ; periodic attributes
Subject RIV	BB - Applied Statistics, Operational Research
R&D Projects	1ET400300513 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
UT WOS	000267117500003
EID SCOPUS	67650703129
DOI	10.1142/S0218001409007338
Annotation	The K-means algorithm is very popular in the machine learning community due to its inherent simplicity. However, in its basic form, it is not suitable for use in problems which contain periodic attributes, such as oscillator phase, hour of day or directional heading. A commonly used technique of trigonometrically encoding periodic input attributes to artificially generate the required topology introduces a systematic error. In this paper, a metric which induces a conceptually correct topology for periodic attributes is embedded into the K-means algorithm. This requires solving a non-convex minimization problem in the maximization step. Results of numerical experiments comparing the proposed algorithm to K-means with trigonometric encoding on synthetically generated data are reported. The advantage of using the proposed K-means algorithm is also shown on a real example using gas load data to build simple predictive models.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2010

Number of the records: 1