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Interpretability Issues in Fuzzy Modeling
J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.)
Table of Contents
Foreword
P. BonissonePreface
J. Casillas, O. Cordón, F. Herrera, L. Magdalena
1. OVERVIEW
Interpretability improvements to find the balance interpretability-accuracy in fuzzy modeling: an overview
J. Casillas, O. Cordón, F. Herrera, L. Magdalena
p. 3
2. IMPROVING THE INTERPRETABILITY WITH FLEXIBLE RULE STRUCTURES
Regaining comprehensibility of approximative fuzzy models via the use of linguistic hedges
J.G. Marín-Blázquez, Q. Shen
p. 25Identifying flexible structured premises for mining concise fuzzy knowledge
N. Xiong, L. Litz
p. 54
3. COMPLEXITY REDUCTION IN LINGUISTIC FUZZY MODELS
A multiobjective genetic learning process for joint feature selection and granularity and contexts learning in fuzzy rule-based classification systems
O. Cordón, M.J. del Jesus, F. Herrera, L. Magdalena, P. Villar
p. 79Extracting linguistic fuzzy models from numerical data-AFRELI algorithm
J. Espinosa, J. Vandewalle
p. 100Constrained optimization of fuzzy decision trees
P.-Y. Glorennec
p. 125A new method for inducing a set of interpretable fuzzy partitions and fuzzy inference systems from data
S. Guillaume, B. Charnomordic
p. 148A feature ranking algorithm for fuzzy modelling problems
D. Tikk, T.D. Gedeon, K.W. Wong
p. 176Interpretability in multidimensional classification
V. Vanhoucke, R. Silipo
p. 193
4. COMPLEXITY REDUCTION IN PRECISE FUZZY MODELS
Interpretable semi-mechanistic fuzzy models by clustering, OLS and FIS model reduction
J. Abonyi, H. Roubos, R. Babuska, F. Szeifert
p. 221Trade-off between approximation accuracy and complexity: TS controller design via HOSVD based complexity minimization
P. Baranyi, Y. Yam, D. Tikk, R.J. Patton
p. 249Simplification and reduction of fuzzy rules
M. Setnes
p. 278Effect of rule representation in rule base reduction
T. Sudkamp, A. Knapp, J. Knapp
p. 303Singular value-based fuzzy reduction with relaxed normalization condition
Y. Yam, C.T. Yang, P. Baranyi
p. 325
5. INTERPRETABILITY CONSTRAINTS IN TSK FUZZY RULE-BASED SYSTEMS
Interpretability, complexity, and modular structure of fuzzy systems
M. Bikdash
p. 355Hierarchical genetic fuzzy systems: accuracy, interpretability and design autonomy
M.R. Delgado, F. von Zuben, F. Gomide
p. 379About the trade-off between accuracy and interpretability of Takagi-Sugeno models in the context of nonlinear time series forecasting
A. Fiordaliso
p. 406Accurate, transparent and compact fuzzy models by multi-objective evolutionary algorithms
F. Jiménez, A.F. Gómez-Skarmeta, G. Sánchez, H. Roubos, R. Babuska
p. 431Transparent fuzzy systems in modeling and control
A. Riid, E. Rüstern
p. 452Uniform fuzzy partitions with cardinal splines and wavelets: getting interpretable linguistic fuzzy models
A.R. de Soto
p. 477
6. ASSESSMENTS ON THE INTERPRETABILITY LOSS
Relating the theory of partitions in MV-logic to the design of interpretable fuzzy systems
P. Amato, C. Manara
p. 499A formal model of interpretability of linguistic variables
U. Bodenhofer, P. Bauer
p. 524Expressing relevance and interpretability of rule-based systems
W. Pedrycz
p. 546Conciseness of fuzzy models
T. Suzuki, T. Furuhashi
p. 568Exact trade-off between approximation accuracy and interpretability: solving the saturation problem for certain FRBSs
D. Tikk, P. Baranyi
p. 587
7. INTERPRETATION OF BLACK-BOX MODELS AS FUZZY RULE-BASED MODELS
Interpretability improvement of RBF-based neurofuzzy systems using regularized learning
Y. Jin
p. 605Extracting fuzzy classification rules from fuzzy clusters on the basis of separating hyperplanes
B. von Schmidt, F. Klawonn
p. 621
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