Sequential Optimization of $$\gamma $$-Decision Rules Relative to Length, Coverage and Number of Misclassifications

DOI10.1007/978-3-662-47815-8_5zbMath1434.68581OpenAlexW2294064920MaRDI QIDQ2947190

Beata Zielosko

Publication date: 22 September 2015

Published in: Transactions on Rough Sets XIX (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-662-47815-8_5

Mathematics Subject Classification ID

Dynamic programming (90C39) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

• Combinatorial machine learning. A rough set approach.
• Rudiments of rough sets
• Rough sets and Boolean reasoning
• Partial covers, reducts and decision rules in rough sets. Theory and applications
• ROC `n' rule learning -- towards a better understanding of covering algorithms
• Dynamic programming approach to optimization of approximate decision rules
• Dynamic Programming Approach for Partial Decision Rule Optimization
• Approximate Boolean Reasoning: Foundations and Applications in Data Mining
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