Title: ADVANCES IN ROBUST CLUSTERING FOR REGRESSION STRUCTURES
Authors: PERROTTA DOMENICOTORTI FRANCESCACERIOLI ANDREARIANI MARCO
Publisher: Universitas Studiorum S.r.l. Casa Editrice
Publication Year: 2017
JRC N°: JRC106435
ISBN: 978-88-99459-71-0
URI: http://www.universitas-studiorum.it/1/cladag_2017_book_of_short_papers_2852494.html
http://publications.jrc.ec.europa.eu/repository/handle/JRC106435
Type: Articles in periodicals and books
Abstract: We investigate the properties of state-of-the-art robust clusterwise regression tools based on trimming and restrictions, under a variety of data configurations and contamination schemes. The data are generated through a new flexible simulation tool for mixtures of regressions, where the user can control the degree of overlap between the groups. The tool is also used to illustrate the effect of concentrated “noise type” contamination on the fit of robust clusterwise regression methods.
JRC Directorate:Joint Research Centre Corporate Activities

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