Multi-objective optimization method for learning thresholds in a decision-theoretic rough set model

DOI10.1016/j.ijar.2016.01.002zbMath1352.68249OpenAlexW2250544991MaRDI QIDQ256483

Yanglong Fan, Tingsheng Yang, Zhanchao Zhang, Jianhua Cao, Ruilin Pan, Ke Lu

Publication date: 9 March 2016

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2016.01.002

zbMATH Keywords

multi-objective optimization\(\mathrm{F}_{-}\)measuredecision-theoretic rough set modelPareto optimal setthreshold learning

Mathematics Subject Classification ID

Decision theory (91B06) Multi-objective and goal programming (90C29) Reasoning under uncertainty in the context of artificial intelligence (68T37)

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Single-parameter decision-theoretic rough set ⋮ Gini objective functions for three-way classifications ⋮ Enhanced cultural algorithm to solve multi-objective attribute reduction based on rough set theory

Cites Work

• Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model
• Attribute reduction in decision-theoretic rough set models
• Probabilistic rough set approximations
• Double-quantitative decision-theoretic rough set
• An automatic method to determine the number of clusters using decision-theoretic rough set
• Analyzing uncertainties of probabilistic rough set regions with game-theoretic rough sets
• On an optimization representation of decision-theoretic rough set model
• Incorporating logistic regression to decision-theoretic rough sets for classifications
• Multi-class decision-theoretic rough sets
• A genetic algorithm for the resource constrained multi-project scheduling problem
• Minimum cost attribute reduction in decision-theoretic rough set models
• Game-Theoretic Rough Sets
• Rough sets: probabilistic versus deterministic approach
• Rough sets
• An Outline of a Theory of Three-Way Decisions
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