The proceedings contain 40 papers. The topics discussed include: from vagueness to rough sets in partial approximation spaces; random probes in computation and assessment of approximate reducts; applications of Boolean kernels in rough sets; robust ordinal regression for dominance-based rough set approach under uncertainty; monotonic uncertainty measures in probabilistic rough set model; attribute subset quality functions over a universe of weighted objects; a rough set approach to novel compounds activity prediction based on surface active properties and molecular descriptors; rough sets in ortholog gene detection; hybrid model based on rough sets theory and fuzzy cognitive maps for decision-making; decision rule classifiers for multi-label decision tables; and considerations on rule induction procedures by STRIM and their relationship to VPRS.
Kryszkiewicz, M., Cornelis, C., Ciucci, D., Medina Moreno, J., Motoda, H., Raś, Z. (a cura di). (2014). Rough Sets and Intelligent Systems Paradigms. Springer [10.1007/978-3-319-08729-0].
Rough Sets and Intelligent Systems Paradigms
CIUCCI, DAVIDE ELIO;
2014
Abstract
The proceedings contain 40 papers. The topics discussed include: from vagueness to rough sets in partial approximation spaces; random probes in computation and assessment of approximate reducts; applications of Boolean kernels in rough sets; robust ordinal regression for dominance-based rough set approach under uncertainty; monotonic uncertainty measures in probabilistic rough set model; attribute subset quality functions over a universe of weighted objects; a rough set approach to novel compounds activity prediction based on surface active properties and molecular descriptors; rough sets in ortholog gene detection; hybrid model based on rough sets theory and fuzzy cognitive maps for decision-making; decision rule classifiers for multi-label decision tables; and considerations on rule induction procedures by STRIM and their relationship to VPRS.
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