Fitting Symmetric Fuzzy Measures for Discrete Sugeno Integration
The Sugeno integral has numerous successful applications, including but not limited to the areas of decision making, preference modeling, and bibliometrics. Despite this, the current state of the development of usable algorithms for numerically fitting the underlying discrete fuzzy measure based on a sample of prototypical values – even in the simplest possible case, i.e., assuming the symmetry of the capacity – is yet to reach a satisfactory level. Thus, the aim of this paper is to present some results and observations concerning this class of data approximation problems.
KeywordsSugeno integral Aggregation functions Machine learning Regression Approximation
This study was supported by the National Science Center, Poland, research project 2014/13/D/HS4/01700. Data provided by Scopus.com.
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