Extracting decision rules from qualitative data using sugeno integral: A case-study

Publication Type:
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9161 pp. 14 - 24
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© Springer International Publishing Switzerland 2015. This paper deals with knowledge extraction from experimental data in multifactorial evaluation using Sugeno integrals. They are qualitative criteria aggregations where it is possible to assign weights to groups of criteria. A method for deriving such weights from data is recalled. We also present results in the logical representation of Sugeno integrals. Then we show how to extract if-then rules expressing the selection of good situations on the basis of local evaluations, and rules to detect bad situations. We illustrate such methods on a case-study in the area of water ecosystem health.
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