@article {article,
	title = {Cost-Sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems Using FURIA},
	journal = {International Journal of Uncertainty Fuzziness and Knowledge-Based Systems},
	volume = {22},
	year = {2014},
	month = {10},
	pages = {643-675},
	doi = {10.1142/S0218488514500330},
	author = {Palacios, Ana and Trawinski, Krzysztof and O. Cord{\'o}n and S{\'a}nchez, Luciano}
}
@conference {10.1007/978-3-319-08644-6_31,
	title = {Selecting the Most Informative Inputs in Modelling Problems with Vague Data Applied to the Search of Informative Code Metrics for Continuous Assessment in Computer Science Online Courses},
	booktitle = {Rough Sets and Current Trends in Computing},
	year = {2014},
	pages = {299{\textendash}308},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Sorting a set of inputs for relevance in modeling problems may be ambiguous if the data is vague. A general extension procedure is proposed in this paper that allows applying different deterministic or random feature selection algorithms to fuzzy data. This extension is based on a model of the relevance of a feature as a possibility distribution. The possibilistic relevances are ordered with the help of a fuzzy ranking. A practical problem where the most informative software metrics are searched for in an automatic grading problem is solved with this technique.},
	isbn = {978-3-319-08644-6},
	author = {Otero, Jos{\'e} and Del Rosario Su{\'a}rez, Maria and Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano},
	editor = {Cornelis, Chris and Kryszkiewicz, Marzena and {\'S}lȩzak, Dominik and Ruiz, Ernestina Menasalvas and Bello, Rafael and Shang, Lin}
}
@conference {inproceedings,
	title = {Supervising classrooms comprising children with dyslexia and other learning problems with graphical exploratory analysis for fuzzy data: Presentation of the software tool and case study},
	booktitle = {IEEE International Conference on Fuzzy Systems},
	year = {2014},
	month = {07},
	pages = {2133-2140},
	doi = {10.1109/FUZZ-IEEE.2014.6891710},
	author = {Palacios, Ana and S{\'a}nchez, Luciano}
}
@article {article,
	title = {A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotorblade leading edge materials},
	journal = {Mechanical Systems and Signal Processing},
	volume = {37},
	year = {2013},
	month = {06},
	pages = {76-91},
	doi = {10.1016/j.ymssp.2012.02.009},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s and Palacios, Ana and Palacios, Jos{\'e}}
}
@article {doi:10.1142/S0218488512400156,
	title = {COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	volume = {20},
	number = {supp02},
	year = {2012},
	pages = {51-71},
	abstract = {An extension of the Adaboost algorithm for obtaining fuzzy rule-based systems from low quality data is combined with preprocessing algorithms for equalizing imbalanced datasets. With the help of synthetic and real-world problems, it is shown that the performance of the Adaboost algorithm is degraded in presence of a moderate uncertainty in either the input or the output values. It is also established that a preprocessing stage improves the accuracy of the classifier in a wide range of binary classification problems, including those whose imbalance ratio is uncertain.},
	doi = {10.1142/S0218488512400156},
	url = {https://doi.org/10.1142/S0218488512400156},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems},
	journal = {Multiple-Valued Logic and Soft Computing},
	volume = {17},
	year = {2011},
	month = {01},
	pages = {207-228},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure},
	booktitle = {International Conference on Intelligent Systems Design and Applications},
	year = {2011},
	month = {11},
	pages = {1391-1396},
	doi = {10.1109/ISDA.2011.6121854},
	author = {Otero, Jos{\'e} and S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data.},
	year = {2009},
	month = {01},
	pages = {803-808},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets},
	journal = {Evolutionary Intelligence},
	volume = {2},
	year = {2009},
	month = {11},
	pages = {73-84},
	doi = {10.1007/s12065-009-0024-1},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {GFS-Based Analysis of Vague Databases in High Performance Athletics},
	year = {2009},
	month = {09},
	pages = {602-609},
	doi = {10.1007/978-3-642-04394-9_73},
	author = {Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia},
	booktitle = {Lecture Notes in Computer Science - LNCS},
	volume = {5271},
	year = {2008},
	month = {09},
	pages = {608-615},
	doi = {10.1007/978-3-540-87656-4_75},
	author = {S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
