C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
ELEM2: A Learning System for More Accurate Classifications
AI '98 Proceedings of the 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Classification Rule Discovery with Ant Colony Optimization
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications
Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Order based genetic algorithms for the search of approximate entropy reducts
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Sequential covering rule induction algorithm for variable consistency rough set approaches
Information Sciences: an International Journal
Decision rule-based data models using TRS and NetTRS – methods and algorithms
Transactions on Rough Sets XI
Approximate boolean reasoning: foundations and applications in data mining
Transactions on Rough Sets V
Paper: Modeling by shortest data description
Automatica (Journal of IFAC)
Dynamic Programming Approach for Partial Decision Rule Optimization
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Dynamic programming approach to optimization of approximate decision rules
Information Sciences: an International Journal
Combinatorial Machine Learning: A Rough Set Approach
Combinatorial Machine Learning: A Rough Set Approach
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The paper describes a new tool for study relationships between length and coverage of exact decision rules. This tool is based on dynamic programming approach. We also present results of experiments with decision tables from UCI Machine Learning Repository.