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Clusterwise regression 3 Alternating least squares algorithm 1 Anti-fraud 1 Bootstrap test 1 Branch and bound 1 CLASSI 1 Clustering 1 Column generation 1 Combinatorial optimization 1 Concentrated noise 1 Finite mixture model 1 Functional linear models 1 Fuzzy clusterwise regression model 1 Global optimization 1 Heuristics 1 International trade 1 Linear regression 1 Orthogonal regression 1 Outlier detection 1 Regularized fuzzy clustering 1 Ridge regression 1 Robust clusterwise regression 1 Robust regression 1 Sequencing 1 TCLUST 1 Thinning 1 Trimming 1 Weighted regression 1 binary data 1 clustering 1 clusterwise regression 1 individual differences 1 sequential processes 1
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Undetermined 6
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Article 6
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Hwang, Heungsun 2 Suk, Hye 2 Caporossi, Gilles 1 Carbonneau, Réal 1 Cerioli, Andrea 1 Ceulemans, Eva 1 Gaer, Eva Vande 1 Hansen, Pierre 1 Kuppens, Peter 1 Lim, Jooseop 1 Mechelen, Iven 1 Perrotta, Domenico 1 Schlittgen, Rainer 1 Tan, Tianyu 1
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Advances in Data Analysis and Classification 3 AStA Advances in Statistical Analysis 1 Journal of Classification 1 Psychometrika 1
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RePEc 6
Showing 1 - 6 of 6
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Globally Optimal Clusterwise Regression By Column Generation Enhanced with Heuristics, Sequencing and Ending Subset Optimization
Carbonneau, Réal; Caporossi, Gilles; Hansen, Pierre - In: Journal of Classification 31 (2014) 2, pp. 219-241
A column generation based approach is proposed for solving the cluster-wise regression problem. The proposed strategy relies firstly on several efficient heuristic strategies to insert columns into the restricted master problem. If these heuristics fail to identify an improving column, an...
Persistent link: https://www.econbiz.de/10010950401
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Robust clustering around regression lines with high density regions
Cerioli, Andrea; Perrotta, Domenico - In: Advances in Data Analysis and Classification 8 (2014) 1, pp. 5-26
Robust methods are needed to fit regression lines when outliers are present. In a clustering framework, outliers can be extreme observations, high leverage points, but also data points which lie among the groups. Outliers are also of paramount importance in the analysis of international trade...
Persistent link: https://www.econbiz.de/10010758714
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Functional fuzzy clusterwise regression analysis
Tan, Tianyu; Suk, Hye; Hwang, Heungsun; Lim, Jooseop - In: Advances in Data Analysis and Classification 7 (2013) 1, pp. 57-82
We propose a functional extension of fuzzy clusterwise regression, which estimates fuzzy memberships of clusters and … variables to be functional, varying over time, space, and other continua. The fuzzy memberships and clusterwise regression …
Persistent link: https://www.econbiz.de/10010634339
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The CLASSI-N Method for the Study of Sequential Processes
Gaer, Eva Vande; Ceulemans, Eva; Mechelen, Iven; … - In: Psychometrika 77 (2012) 1, pp. 85-105
Persistent link: https://www.econbiz.de/10009400063
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A weighted least-squares approach to clusterwise regression
Schlittgen, Rainer - In: AStA Advances in Statistical Analysis 95 (2011) 2, pp. 205-217
Persistent link: https://www.econbiz.de/10009149508
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Regularized fuzzy clusterwise ridge regression
Suk, Hye; Hwang, Heungsun - In: Advances in Data Analysis and Classification 4 (2010) 1, pp. 35-51
Persistent link: https://www.econbiz.de/10008486741
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