Table of Contents for: Cluster analysis for data mining and sys

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Cluster analysis for data mining and system identification /

János Abonyi, Balázs Feil.

Book Cover
Main Author: Abonyi, Janos
Other Names: Feil, Balázs.
Published: Basel ; Birkhäuser, ©2007.
Topics: Cluster analysis. | Data mining. | System identification. | Data mining. | System identification. | Cluster analysis.
Genres: Electronic books.
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Cover -- TOC36;Contents -- Preface -- CH36;1 Classical Fuzzy Cluster Analysis -- 146;1 Motivation -- 146;2 Types of Data -- 146;3 Similarity Measures -- 146;4 Clustering Techniques -- 146;446;1 Hierarchical Clustering Algorithms -- 146;446;2 Partitional Algorithms -- 146;5 Fuzzy Clustering -- 146;546;1 Fuzzy partition -- 146;546;2 The Fuzzy c45;Means Functional -- 146;546;3 Ways for Realizing Fuzzy Clustering -- 146;546;4 The Fuzzy c45;Means Algorithm -- 146;546;5 Inner45;Product Norms -- 146;546;6 GustafsonKessel Algorithm -- 146;546;7 GathGeva Clustering Algorithm -- 146;6 Cluster Analysis of Correlated Data -- 146;7 Validity Measures -- CH36;2 Visualization of the Clustering Results -- 246;1 Introduction58; Motivation and Methods -- 246;146;1 Principal Component Analysis -- 246;146;2 Sammon Mapping -- 246;146;3 Kohonen Self45;Organizing Maps -- 246;2 Fuzzy Sammon Mapping -- 246;246;1 Modified Sammon Mapping -- 246;246;2 Application Examples -- 246;246;3 Conclusions -- 246;3 Fuzzy Self45;Organizing Map -- 246;346;1 Regularized Fuzzy c45;Means Clustering -- 246;346;2 Case Study -- 246;346;3 Conclusions -- CH36;3 Clustering for Fuzzy Model Identification Regression -- 346;1 Introduction to Fuzzy Modelling -- 346;2 TakagiSugeno 40;TS41; Fuzzy Models -- 346;246;1 Structure of Zero45; and First45;order TS Fuzzy Models -- 346;246;2 Related Modelling Paradigms -- 346;3 TS Fuzzy Models for Nonlinear Regression -- 346;346;1 Fuzzy Model Identification Based on GathGeva Clustering -- 346;346;2 Construction of Antecedent Membership Functions -- 346;346;3 Modified GathGeva Clustering -- 346;346;4 Selection of the Antecedent and Consequent Variables -- 346;346;5 Conclusions -- 346;4 Fuzzy Regression Tree -- 346;446;1 Preliminaries -- 346;446;2 Identification of Fuzzy Regression Trees based on Clustering Algorithm -- 346;446;3 Conclusions -- 346;5 Clustering for Structure Selection -- 346;546;1 Introduction -- 346;546;2 Input Selection for Discrete Data -- 346;546;3 Fuzzy Clustering Approach to Input Selection -- 346;546;4 Examples -- 346;546;5 Conclusions -- CH36;4 Fuzzy Clustering for System Identification -- 446;1 Data45;Driven Modelling of Dynamical Systems -- 446;146;1 TS Fuzzy Models of SISO and MIMO Systems -- 446;146;2 Clustering for the Identification of MIMO Processes -- 446;146;3 Conclusions -- 446;2 Semi45;Mechanistic Fuzzy Models -- 446;246;1 Introduction to Semi45;Mechanistic Modelling -- 446;246;2 Structure of the Semi45;Mechanistic Fuzzy Model -- 446;246;3 Clustering45;based Identification of the Semi45;Mechanistic Fuzzy Model -- 446;246;4 Conclusions -- 446;3 Model Order Selection -- 446;346;1 Introduction -- 446;346;2 FNN Algorithm -- 446;346;3 Fuzzy Clustering based FNN -- 446;346;4 Cluster Analysis based Direct Model Order Estimation -- 446;346;5 Application Examples -- 446;346;6 Conclusions -- 446;4 State45;Space Reconstruction -- 446;446;1 Introduction -- 446;446;2 Clustering45;based Approach to State45;space Reconstruction -- 446;446;3 Application Examples and Discussion -- 446;446;4 Case Stu.
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Table of Contents for: Cluster analysis for data mining and sys