Abstract
Knowledge discovered from data tables is often presented in terms of “if. . .then. . .” decision rules. With each rule a confidence measure is associated. We present a method for measuring importance of each single condition or interactions among groups of conditions in the “if” part of the rules. The methodology is based on some indices introduced in literature to analyze fuzzy measures.
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CITATION STYLE
Greco, S., Matarazzo, B., SŁOwiński, R., & Stefanowski, J. (2002). Importance and interaction of conditions in decision rules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2475, pp. 255–262). Springer Verlag. https://doi.org/10.1007/3-540-45813-1_33
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