Interpretability Issues in Fuzzy Modeling
J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.)
Table of Contents
Foreword
P. Bonissone
pp. V-VII
Preface
J. Casillas, O. Cordón, F. Herrera, L. Magdalena
pp. IX-X
1. OVERVIEW
Interpretability improvements to find the balance interpretability-accuracy in fuzzy modeling: an overview
J. Casillas, O. Cordón, F. Herrera, L. Magdalena
pp. 3-22
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
pp. 25-53
Identifying flexible structured premises for mining concise fuzzy knowledge
N. Xiong, L. Litz
pp. 54-76
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
pp. 79-99
Extracting linguistic fuzzy models from numerical data-AFRELI algorithm
J. Espinosa, J. Vandewalle
pp. 100-124
Constrained optimization of fuzzy decision trees
P.-Y. Glorennec
pp. 125-147
A new method for inducing a set of interpretable fuzzy partitions and fuzzy inference systems from data
S. Guillaume, B. Charnomordic
pp. 148-175
A feature ranking algorithm for fuzzy modelling problems
D. Tikk, T.D. Gedeon, K.W. Wong
pp. 176-192
Interpretability in multidimensional classification
V. Vanhoucke, R. Silipo
pp. 193-217
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
pp. 221-248
Trade-off between approximation accuracy and complexity: TS controller design via HOSVD based complexity minimization
P. Baranyi, Y. Yam, D. Tikk, R.J. Patton
pp. 249-277
Simplification and reduction of fuzzy rules
M. Setnes
pp. 278-302
Effect of rule representation in rule base reduction
T. Sudkamp, A. Knapp, J. Knapp
pp. 303-324
Singular value-based fuzzy reduction with relaxed normalization condition
Y. Yam, C.T. Yang, P. Baranyi
pp. 325-352
5. INTERPRETABILITY CONSTRAINTS IN TSK FUZZY RULE-BASED SYSTEMS
Interpretability, complexity, and modular structure of fuzzy systems
M. Bikdash
pp. 355-378
Hierarchical genetic fuzzy systems: accuracy, interpretability and design autonomy
M.R. Delgado, F. von Zuben, F. Gomide
pp. 379-405
About the trade-off between accuracy and interpretability of Takagi-Sugeno models in the context of nonlinear time series forecasting
A. Fiordaliso
pp. 406-430
Accurate, transparent and compact fuzzy models by multi-objective evolutionary algorithms
F. Jiménez, A.F. Gómez-Skarmeta, G. Sánchez,
H. Roubos, R. Babuska
pp. 431-451
Transparent fuzzy systems in modeling and control
A. Riid, E. Rüstern
pp. 452-476
Uniform fuzzy partitions with cardinal splines and wavelets: getting interpretable linguistic fuzzy models
A.R. de Soto
pp. 477-495
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
pp. 499-523
A formal model of interpretability of linguistic variables
U. Bodenhofer, P. Bauer
pp. 524-545
Expressing relevance and interpretability of rule-based systems
W. Pedrycz
pp. 546-567
Conciseness of fuzzy models
T. Suzuki, T. Furuhashi
pp. 568-586
Exact trade-off between approximation accuracy and interpretability: solving the saturation problem for certain FRBSs
D. Tikk, P. Baranyi
pp. 587-601
7. INTERPRETATION OF BLACK-BOX MODELS AS FUZZY RULE-BASED MODELS
Interpretability improvement of RBF-based neurofuzzy systems using regularized learning
Y. Jin
pp. 605-620
Extracting fuzzy classification rules from fuzzy clusters on the basis of separating hyperplanes
B. von Schmidt, F. Klawonn
pp. 621-643