Boosted-oriented probabilistic smoothing-spline clustering of series

DOI10.1007/s10260-022-00665-yarXiv1507.04905MaRDI QIDQ6067169

Gianluca Frasso, Antonio D'Ambrosio, Carmela Iorio, Roberta Siciliano

Publication date: 14 December 2023

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1507.04905

zbMATH Keywords

fuzzy clusteringboostingcluster validityprobabilistic distance clustering

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Analysis of parameter selections for fuzzy \(c\)-means
• Probabilistic d-clustering
• A periodogram-based metric for time series classification
• \(k\)-mean alignment for curve clustering
• A practical guide to splines
• A decision-theoretic generalization of on-line learning and an application to boosting
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data
• Adjusted concordance index: an extensionl of the adjusted rand index to fuzzy partitions
• Geometric representation of association between categories
• The power of monitoring: how to make the most of a contaminated multivariate sample
• The power of (extended) monitoring in robust clustering. Discussion of ``The power of monitoring: how to make the most of a contaminated multivariate sample
• A fuzzy approach to robust regression clustering
• L- and V-curves for optimal smoothing
• Fuzzy sets
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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