Fuzzy sets, rough sets, multisets and clustering
"This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four … celý popis
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- Fyzický popis
- 1 online zdroj (x, 347 stran) : ilustrace (některé barevné)
- Vydáno
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Cham, Switzerland :
Springer,
[2017]
- Edice
- Studies in computational intelligence
- Témata
- Bibliografie
- Obsahuje bibliografické odkazy
- ISBN
- 978-3-319-47557-8
- Obsah
- On This Book: Clustering, Multisets, Rough Sets and Fuzzy Sets -- Part I Clustering and Classification -- Contributions of Fuzzy Concepts to Data Clustering -- Fuzzy Clustering/Co-clustering and Probabilistic Mixture Models-induced Algorithms -- Semi-Supervised Fuzzy c-Means Algorithms by Revising Dissimilarity/Kernel Matrices -- Various Types of Objective-Based Rough Clustering -- On Some Clustering Algorithms Based on Tolerance -- Robust Clustering Algorithms Employing Fuzzy-Possibilistic Product Partition -- Consensus-based agglomerative hierarchical clustering -- Using a reverse engineering type paradigm in clustering. An evolutionary pro-gramming based approach -- On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data -- Experiences using Decision Trees for Knowledge Discovery -- Part II Bags, Fuzzy Bags, and Some Other Fuzzy Extensions -- L-Fuzzy Bags -- A Perspective on Differences Between Atanassov’s Intuitionistic Fuzzy Sets and Interval-valued Fuzzy Sets -- Part III Rough Sets -- Attribute Importance Degrees Corresponding to Several Kinds of Attribute Reduction in the Setting of the Classical Rough Sets -- A Review on Rough Set-based Interrelationship Mining -- Part IV Fuzzy Sets and Decision Making -- OWA Aggregation of Probability Distributions Using the Probabilistic Exceedance Method -- A Dynamic Average Value-at-Risk Portfolio Model with Fuzzy Random Variables -- Group Decision Making: Consensus Approaches based on Soft Consensus Measures -- Construction of Capacities from Overlap Indexes -- Clustering Alternatives and Learning Preferences Based on Decision Attitudes and Weighted Overlap Dominance
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