Who Cited It

Unsupervised K-Means Clustering Algorithm

2020 · IEEE Access · 2,240 citations · 1 from inside this corpus

Kristina P. Sinaga, Miin‐Shen Yang

The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the k-means algorithm and its extensions are always influenced by initializations with a necessary number of clusters a priori. That is, the k-means algorithm is not exactly an unsupervised clustering method. In this paper, we construct an unsupervised learning schema for the k-means algorithm so that it is free of initializations without parameter selection and can also simultaneously find an optimal number of clusters. That is, we propose a novel unsupervised k-means (U-k-means) clustering algorithm with automatically finding an optimal number of clusters without giving any initialization and parameter selection. The computational complexity of the proposed U-k-means clustering algorithm is also analyzed. Comparisons between the proposed U-k-means and other existing methods are made. Experimental results and comparisons actually demonstrate these good aspects of the proposed U-k-means clustering algorithm.

Unsupervised K-Means Clustering Algorithm (2020)Unsupervised K-Means Clusteri…Data clustering: 50 years beyond K-means (2009)Data clustering: 50 years bey…A Cluster Separation Measure (1979)A Cluster Separation MeasureAlgorithms for Clustering Data (1990)Algorithms for Clustering DataFinding Groups in Data (1990)Finding Groups in DataAlgorithms for clustering data (1989)Algorithms for clustering dataClustering by fast search and find of density peaks (2014)Clustering by fast search and…On Clustering Validation Techniques (2001)On Clustering Validation Tech…Bayes Factors (1995)Bayes FactorsUnsupervised learning of finite mixture models (2002)Unsupervised learning of fini…Mixture models : inference and applications to clustering (1988)Mixture models : inference an…K-means clustering algorithms: A comprehensive review, variants analysis, and advances in… (2022)K-means clustering algorithms…
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What this paper cites, inside the corpus

PaperYearCited
Data clustering: 50 years beyond K-means20099,368
A Cluster Separation Measure19799,060
Algorithms for Clustering Data19907,849
Finding Groups in Data19907,270
Algorithms for clustering data19896,473
Clustering by fast search and find of density peaks20145,040
On Clustering Validation Techniques20012,674
Bayes Factors19952,355
Unsupervised learning of finite mixture models20022,139
Mixture models : inference and applications to clustering19882,079

What cites it, inside the corpus

PaperYearCited
K-means clustering algorithms: A comprehensive review, variants analysis, and advances in…20222,213

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DOI · Open access copy · OpenAlex record

Topics

Advanced Clustering Algorithms ResearchComputer Science
Face and Expression RecognitionComputer Science
Data Mining Algorithms and ApplicationsComputer Science

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  • supports43 reference(s) recorded.
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