A Data-Driven Parameter Adaptive Clustering Algorithm Based on Density Peak

Clustering is an important unsupervised machine learning method which can efficiently partition points without training data set. However, most of the existing clustering algorithms need to set parameters artificially, and the results of clustering are much influenced by these parameters, so optimiz...

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Vydané v:	Complexity (New York, N.Y.) Ročník 2018; číslo 2018; s. 1 - 14
Hlavní autori:	Du, Tao, Wang, Qin, Qu, Shouning
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cairo, Egypt Hindawi Publishing Corporation 01.01.2018 Hindawi John Wiley & Sons, Inc Wiley
Predmet:	Adaptive algorithms Algorithms Clustering Complexity Datasets Density Efficiency Information science Knowledge discovery Machine learning Neighborhoods Parameters Pattern recognition Principal components analysis Specific gravity
ISSN:	1076-2787, 1099-0526
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