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Fitting fuzzy measures by linear programming. Programming library fmtools

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conference contribution
posted on 2008-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov
We discuss the problem of learning fuzzy measures from empirical data. Values of the discrete Choquet integral are fitted to the data in the least absolute deviation sense. This problem is solved by linear programming techniques. We consider the cases when the data are given on the numerical and interval scales. An open source programming library which facilitates calculations involving fuzzy measures and their learning from data is presented.

History

Event

IEEE International Conference on Fuzzy Systems (17th : 2008 : Hong Kong)

Pagination

862 - 867

Publisher

IEEE

Location

Hong Kong

Place of publication

Piscataway, N.J.

Start date

2008-06-01

End date

2008-06-06

ISSN

1098-7584

ISBN-13

9781424418190

Language

eng

Notes

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Publication classification

E1 Full written paper - refereed; E Conference publication

Copyright notice

2008, IEEE.

Editor/Contributor(s)

G Feng

Title of proceedings

2008 IEEE International Conference on Fuzzy Systems : proceedings : FUZZ-IEEE 2008