k-order additive discrete fuzzy measures and their representation
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Rough Sets and Decision Algorithms
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
An Analysis of Quantitative Measures Associated with Rules
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
An empirical study of using rule induction and rough sets to software cost estimation
Fundamenta Informaticae - Special issue on theory and applications of soft computing (TASC04)
Evaluating Importance of Conditions in the Set of Discovered Rules
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Redefinition of Decision Rules Based on the Importance of Elementary Conditions Evaluation
Fundamenta Informaticae
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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.