Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Rough Sets: The Experts Speak -- Decision-Oriented Rough Set Methods -- 1 Introduction -- 2 Decision-Oriented Rough Set Models and Methods -- 3 Concluding Remarks and Future Perspectives -- References -- On Generalized Decision Functions: Reducts, Networks and Ensembles -- 1 Introduction -- 2 Generalized Decision Functions -- 3 Simplified Conditional Independence -- 4 Generalized Decision Measures -- 5 Embedded Decision Reducts -- 6 Ensembles of Complementary Reducts -- 7 Attribute Decomposition Problem -- 8 Heuristics and Boolean Representation -- 9 Conclusions and Future Directions -- References -- Formalization of Medical Diagnostic Rules -- 1 Introduction -- 2 Background: Medical Diagnostic Process -- 2.1 RHINOS -- 2.2 Focusing Mechanism -- 3 Basics of Rule Definitions -- 3.1 Rough Sets -- 3.2 Classification Accuracy and Coverage -- 3.3 Probabilistic Rules -- 4 Formalization of Medical Diagnostic Rules -- 4.1 Deterministic Model -- 4.2 Probabilistic Model -- 5 New Rule Induction Model -- 6 Discussion: What Has Not Been Achieved? -- 7 Conclusion -- References -- Multi-granularity Intelligent Information Processing -- 1 Introduction -- 2 Multi-granularity Rough Set Theory -- 3 Multi-granularity Computing with Words -- 4 Multi-granularity Fuzzy Quotient Space Theory -- 5 Multi-granularity Cloud Model -- 6 Multi-granularity Clustering Based on Density Peaks -- 7 Conclusion -- References -- Granular Structures Induced by Interval Sets and Rough Sets -- 1 Introduction -- 2 Interval Sets -- 2.1 Interval Sets and Interval-Set Algebras -- 2.2 Inclusion Relations in Interval Sets -- 2.3 Granular Structure in Interval Sets -- 3 The Granular Structure Based on Order Relation in Interval Sets -- 3.1 Preference -- 3.2 Interval Set Comparisons

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