The MinMax k-Means clustering algorithm

Applying k-Means to minimize the sum of the intra-cluster variances is the most popular clustering approach. However, after a bad initialization, poor local optima can be easily obtained. To tackle the initialization problem of k-Means, we propose the MinMax k-Means algorithm, a method that assigns...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Pattern recognition Ročník 47; číslo 7; s. 2505 - 2516
Hlavní autoři:	Tzortzis, Grigorios, Likas, Aristidis
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.07.2014 Elsevier
Témata:	Algorithms Applied sciences Balanced clusters Cluster analysis Clustering Clusters Emergence Exact sciences and technology Information, signal and communications theory k-Means k-Means initialization Pattern recognition Robustness Signal and communications theory Signal representation. Spectral analysis Signal, noise Telecommunications and information theory Variance Weighting k-Means initialization Balanced clusters Clustering k-Means Performance evaluation Automatic classification Weighting Minimax method Iterative method K means algorithm Robustness Signal classification
ISSN:	0031-3203, 1873-5142
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!