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Clustrimi Robust K-mesjetash×Analiza e Grupeve (Cluster Analysis)×
FushaStatistikëStatistikë
FamiljaLatent structureLatent structure
Viti i origjinës19971939–1967
KrijuesiCuesta-Albertos, Gordaliza & MatránRobert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-means
LlojiRobust partitional clusteringUnsupervised classification / grouping
Burimi themeluesCuesta-Albertos, J. A., Gordaliza, A., & Matrán, C. (1997). Trimmed k-means: An attempt to robustify quantizers. The Annals of Statistics, 25(2), 553–576. DOI ↗Everitt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913
Emërtime të tjeratrimmed k-means, TCLUST k-means, contamination-resistant k-means, outlier-robust clusteringclustering, unsupervised classification, data clustering, numerical taxonomy
Të lidhura45
PërmbledhjaRobust K-means clustering is an extension of classical k-means that protects cluster estimates from distortion caused by outliers or contaminated observations. By trimming a user-specified fraction of the most extreme points before updating cluster centers, the algorithm yields stable, meaningful partitions even when the data contain atypical cases that would severely bias standard k-means.Cluster analysis is a family of unsupervised multivariate techniques that partition a set of objects or observations into internally homogeneous, mutually distinct groups — clusters — based on measured characteristics, without any prior knowledge of group membership. It is widely used in market segmentation, bioinformatics, psychology, and social science to reveal natural groupings in data.
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ScholarGateKrahasoni metodat: Robust K-means Clustering · Cluster Analysis. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare