Time Series Clustering Based on the K-Means Algorithm

Autor:	V. Lyashenko, Oleg Kobylin
Rok vydání:	2020
Předmět:	ComputingMethodologies_PATTERNRECOGNITION Series (mathematics) Computer science k-means clustering Cluster analysis Algorithm
Zdroj:	Journal La Multiapp. 1:1-7
ISSN:	2721-1290 2716-3865
DOI:	10.37899/journallamultiapp.v1i3.191
Popis:	Time series is one of the forms of data presentation that is used in many studies. It is convenient, easy and informative. Clustering is one of the tasks of data processing. Thus, the most relevant currently are methods for clustering time series. Clustering time series data aims to create clusters with high similarity within a cluster and low similarity between clusters. This work is devoted to clustering time series. Various methods of time series clustering are considered. Examples are given for real data.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::35617141ba11e37314b694a1e97f43d5 https://doi.org/10.37899/journallamultiapp.v1i3.191 Zobrazit plný text záznamu