Fitting fuzzy measures by linear programming. Programming library fmtools


Autoria(s): Beliakov, Gleb
Contribuinte(s)

Feng, Gary G.

Data(s)

01/01/2008

Resumo

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. <br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30018287

Idioma(s)

eng

Publicador

IEEE

Relação

http://dro.deakin.edu.au/eserv/DU:30018287/beliakov-fittingfuzzymeasures-2008.pdf

http://dx.doi.org/10.1109/FUZZY.2008.4630471

Direitos

2008, IEEE.

Palavras-Chave #data analysis #fuzzy systems #learning (artificial intelligence) #linear programming
Tipo

Conference Paper