@article {article,
	title = {Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability{\textendash}Accuracy Trade-off},
	journal = {International Journal of Approximate Reasoning},
	volume = {44},
	year = {2007},
	month = {01},
	pages = {1-3},
	doi = {10.1016/j.ijar.2006.06.002},
	author = {Casillas, Jorge and F. Herrera and P{\'e}rez, Ra{\'u}l and Villar, P}
}
@inbook {Cord{\'o}n2003,
	title = {A Multiobjective Genetic Learning Process for joint Feature Selection and Granularity and Contexts Learning in Fuzzy Rule-Based Classification Systems},
	booktitle = {Interpretability Issues in Fuzzy Modeling},
	year = {2003},
	pages = {79{\textendash}99},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {In this contribution, we propose a genetic process to select an appropiate set of features in a Fuzzy Rule-Based Classification System (FRBCS) and to automatically learn the whole Data Base definition using a non linear scaling function to adapt the fuzzy partition contexts and determining an appropiate granularity for each of them. An ad-hoc data covering learning method is considered to obtain the Rule Base. The method uses a multiobjective genetic algorithm in order to obtain a good trade-off between accuracy and interpretability.},
	isbn = {978-3-540-37057-4},
	doi = {10.1007/978-3-540-37057-4_4},
	url = {https://doi.org/10.1007/978-3-540-37057-4_4},
	author = {O. Cord{\'o}n and M. J. del Jesus and F. Herrera and Magdalena, Luis and Villar, Pedro},
	editor = {Casillas, Jorge and O. Cord{\'o}n and F. Herrera and Magdalena, Luis}
}
@inbook {S{\'a}nchez2003,
	title = {Tuning fuzzy partitions or assigning weights to fuzzy rules: which is better?},
	booktitle = {Accuracy Improvements in Linguistic Fuzzy Modeling},
	year = {2003},
	pages = {366{\textendash}385},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {The accuracy of linguistic classifiers can be improved with several techniques, but they all compromise the interpretability of the rule base up to a certain degree. Assigning weights to fuzzy rules and tuning the memberships associated to linguistic variables are two of the most common methods. In this work we study whether tuning the membership functions in a linguistic classifier is better or not than adjusting rule weights, in terms of the interpretability of the rule base and the complexity of the output.},
	isbn = {978-3-540-37058-1},
	doi = {10.1007/978-3-540-37058-1_15},
	url = {https://doi.org/10.1007/978-3-540-37058-1_15},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e}},
	editor = {Casillas, Jorge and O. Cord{\'o}n and F. Herrera and Magdalena, Luis}
}
