Integrating robust clustering techniques in S-PLUS

DOI10.1016/S0167-9473(97)00020-0zbMath0900.62328OpenAlexW2032190020WikidataQ127248925 ScholiaQ127248925MaRDI QIDQ1389605

Anja Struyf, Peter J. Rousseeuw, Mia Hubert

Publication date: 30 June 1998

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(97)00020-0

zbMATH Keywords

Fuzzy clusteringObject-oriented programmingGraphicsStatistical softwareMedoids

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Functional dimension reduction based on fuzzy partition and transformation, A new dissimilarity measure in time-dependent experiments, MCS: A method for finding the number of clusters, Estimating the mixing proportion in a semiparametric mixture model, Phase and amplitude-based clustering for functional data, A sequential clustering algorithm with applications to gene expression data, A toolbox for \(K\)-centroids cluster analysis, Point set stratification and Delaunay depth, S-PLUS, Displaying a clustering with CLUSPLOT., H-CLAP: hierarchical clustering within a linear array with an application in genetics, Minimization subproblems and heuristics for an applied clustering problem

Uses Software

• Silhouettes
• AS 136

Cites Work

• Unnamed Item
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• Algorithm AS 136: A K-Means Clustering Algorithm
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Numerical methods for fuzzy clustering
• Finding Groups in Data
• Dissimilarity Analysis: a new Technique of Hierarchical Sub-division