Fitting fuzzy measures by linear programming. Programming library fmtools
Contribuinte(s) |
Feng, Gary G. |
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Data(s) |
01/01/2008
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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 | |
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 |