About: K-Means Clustering for Problems with Periodic Attributes

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	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. 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. (en)
Title	K-Means Clustering for Problems with Periodic Attributes K-Means Clustering for Problems with Periodic Attributes (en)
skos:prefLabel	K-Means Clustering for Problems with Periodic Attributes K-Means Clustering for Problems with Periodic Attributes (en)
skos:notation	RIV/67985807:_____/09:00328432!RIV10-AV0-67985807
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1ET400300513), Z(AV0Z10300504)
http://linked.open...iv/cisloPeriodika	4
http://linked.open...vai/riv/dodaniDat	2010
http://linked.open...aciTvurceVysledku	Vejmelka, Martin Paluš, Milan Pelikán, Emil
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav informatiky AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	321878
http://linked.open...ai/riv/idVysledku	RIV/67985807:_____/09:00328432
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	clustering algorithms; similarity measures; K-means; periodic attributes (en)
http://linked.open.../riv/klicoveSlovo	clustering algorithms periodic attributes K-means similarity measures
http://linked.open...odStatuVydavatele	SG - Singapurská republika
http://linked.open...ontrolniKodProRIV	[E1374372C488]
http://linked.open...i/riv/nazevZdroje	International Journal of Pattern Recognition and Artificial Intelligence
http://linked.open...in/vavai/riv/obor	BB
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Mathematical modelling of natural gas consumption for small and middle clients
http://linked.open...UplatneniVysledku	2009
http://linked.open...v/svazekPeriodika	23
http://linked.open...iv/tvurceVysledku	Musílek, P. Paluš, Milan Vejmelka, Martin Pelikán, Emil
http://linked.open...ain/vavai/riv/wos	000267117500003
http://linked.open...n/vavai/riv/zamer	Informatika pro informační společnost: modely, algoritmy, aplikace
issn	0218-0014
number of pages	23 (xsd:int)

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