Titlebook: Combinatorial Machine Learning; A Rough Set Approach Mikhail Moshkov,Beata Zielosko Book 2011 Springer Berlin Heidelberg 2011 Combinatorial

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Mikhail Moshkov,Beata ZieloskoA rough set approach to combinatorial machine learning.Presents applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis and pattern recogniti

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Combinatorial Machine Learning978-3-642-20995-6Series ISSN 1860-949X Series E-ISSN 1860-9503

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978-3-642-26901-1Springer Berlin Heidelberg 2011

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Updates in Pediatric Sleep Apnea,on tables..After that we concentrate on consideration of simple examples from different areas of applications: fault diagnosis, computational geometry, pattern recognition, discrete optimization and analysis of experimental data..These examples allow us to clarify relationships between problems and

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Sleep Deprivation and Pregnancytables with many-valued decisions each row is labeled with a nonempty finite set of natural numbers (decisions). If we want to find all decisions corresponding to a row, we deal with the same mathematical object as decision table with one-valued decisions: it is enough to code different sets of deci