Forward-Stagewise Clustering: An Algorithm for Convex Clustering
Citation:
Zhang, M., Forward-Stagewise Clustering: An Algorithm for Convex Clustering, Pattern Recognition Letters, 2019, 128, 283 - 289Download Item:

Abstract:
This paper proposes an exceptionally simple algorithm, called forward-stagewise clustering, for convex clustering. Convex clustering has drawn recent attention since it nicely addresses the instability issue of traditional non-convex clustering methods. While existing algorithms can precisely solve convex clustering problems, they are sophisticated and produce (agglomerative) clustering paths that contain splits. This motivates us to propose an algorithm that only produces no-split clustering paths.The approach undertaken here follows the line of research initiated in the area of regression. Specifically, we apply the forward-stagewise technique to clustering problems and prove that the algorithm can only produce no-split clustering paths. We then modify the forward-stagewise clustering algorithm to deal with noise and outliers. We further suggest rules of thumb for the algorithm to be applicable to cases where clusters are non-convex. The performance of the proposed algorithm is evaluated through simulations and a real data application.
Author's Homepage:
http://people.tcd.ie/zhangm3Description:
PUBLISHED
Author: Zhang, Mimi
Type of material:
Journal ArticleCollections:
Series/Report no:
Pattern Recognition Letters;128;
Availability:
Full text availableKeywords:
Algorithms, Forward-stagewise clustering, Convex clustering, Fusion penalty, Generalized lasso, Hierarchical clustering, K-nearest neighborISSN:
0167-8655Licences:
Related items
Showing items related by title, author, creator and subject.
-
Clusters in Ireland : the Irish dairy processing industry: an application of Porter's cluster analysis
O'Connell, Larry; Van Egeraat, Chris; Enright, Pat (National Economic and Social Council, ireland, 1997-11) -
Creative Clusters : Economic Analysis of the Current Status and Future Clustering Potential for the Crafts Industry in Ireland
Crafts Council of Ireland; Indecon International Economic Consultants (Crafts Council of Ireland, ireland, 2013-10) -
Ontology Discovery for the Semantic Web Using Hierarchical Clustering
Clerkin, Patrick; Cunningham, Padraig; Hayes, Conor (Trinity College Dublin, Department of Computer Science, 2002-04)According to a proposal by Tim Berners-Lee, the World Wide Web should be extended to make a Semantic Web where human understandable content is structured in such a way as to make it machine processable. Central ...