Ana M. Palacios

发表

Eliciting a human understandable model of ice adhesion strength for rotor blade leading edge materials from uncertain experimental data

Luciano Sánchez, Ana M. Palacios, José Luis Palacios, 2012, Expert Syst. Appl..

Cost-Sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems Using FURIA

Oscar Cordón, Luciano Sánchez, Ana M. Palacios, 2014, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Boosting fuzzy rules with low quality data in multi-class problems: Open problems and challenges

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2013, 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

Finding informative code metrics under uncertainty for predicting the pass rate of online courses

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2016, Inf. Sci..

Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2011, J. Multiple Valued Log. Soft Comput..

Diagnosis of dyslexia with low quality data with genetic fuzzy systems

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2010, Int. J. Approx. Reason..

A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2009, IFSA/EUSFLAT Conf..

CI-LQD: A software tool for modeling and decision making with Low Quality Data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Linguistic cost-sensitive learning of genetic fuzzy classifiers for imprecise data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2011, Int. J. Approx. Reason..

GFS-Based Analysis of Vague Databases in High Performance Athletics

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2009, IDEAL.

Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Graphical exploratory analysis of vague data in the early diagnosis of dyslexia

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2008 .

Mining fuzzy association rules from low-quality data

Jesús Alcalá-Fdez, Ana M. Palacios, María José Gacto, 2012, Soft Comput..

A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotor blade leading edge materials

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2013 .

Sequential pattern mining applied to aeroengine condition monitoring with uncertain health data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2015, Eng. Appl. Artif. Intell..

Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2009, Evol. Intell..

A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2008, HAIS.

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2012, Int. J. Comput. Intell. Syst..

An Extension of the FURIA Classification Algorithm to Low Quality Data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2013, HAIS.

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

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2014, RSCTC.

A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia

Ana M. Palacios, Alberto Márquez, Luis M. Escudero, 2020, bioRxiv.

Bootstrap analysis of multiple repetitions of experiments using an interval-valued multiple comparison procedure

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2014, J. Comput. Syst. Sci..

Mining fuzzy association rules from low-quality data

Jesús Alcalá-Fdez, Luciano Sánchez, Ana M. Palacios, 2011, Soft Computing.

Preprocessing vague imbalanced datasets and its use in genetic fuzzy classifiers

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2010, International Conference on Fuzzy Systems.

Boosting of Fuzzy Rules with Low Quality Data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2012, J. Multiple Valued Log. Soft Comput..

Using the Adaboost algorithm for extracting fuzzy rules from low quality data: Some preliminary results

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

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

Luciano Sánchez, Ana M. Palacios, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A Minimum-Risk Genetic Fuzzy Classifier Based on Low Quality Data

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2009, HAIS.

An extension of the FURIA classification algorithm to low quality data through fuzzy rankings and its application to the early diagnosis of dyslexia

Sébastien Destercke, Inés Couso, Luciano Sánchez, 2016, Neurocomputing.

First study of the behaviour of genetic fuzzy classifier based on low quality data respect to the preprocessing of low quality imbalanced datasets

Ana M. Palacios, I. Couso, L. Sánchez, 2010 .

COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS

Inés Couso, Luciano Sánchez, Ana M. Palacios, 2012 .

Managing stochastic algorithms CV variability using an interval valued multiple comparison procedure

Ana M. Palacios, J. Otero, I. Couso, 2011 .

Mining fuzzy association rules from low-quality data

Ana M. Palacios, J. Alcalá-Fdez, M. J. Gacto, 2011, Soft Computing.