A Proposal of Evolutionary Prototype Selection for Class Imbalance Problems. - Salvador García 001; José Ramón Cano; Alberto Fernández 001; Francisco Herrera (IDEAL, 2006)

A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets. - Alberto Fernández 001; Salvador García 001; María José del Jesus; Francisco Herrera (IWANN, 2007)

An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets. - Alberto Fernández 001; Salvador García 001; Francisco Herrera; María José del Jesus (WILF, 2007)

KEEL: A data mining software tool integrating genetic fuzzy systems. - Jesús Alcalá-Fdez; Salvador García 001; Francisco José Berlanga; Alberto Fernández 001; Luciano Sánchez; María José del Jesus; Francisco Herrera (GEFS, 2008)

A Short Study on the Use of Genetic 2-Tuples Tuning for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (HIS, 2008)

A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets. - Alberto Fernández 001; Salvador García 001; María José del Jesus; Francisco Herrera (Fuzzy Sets Syst., 2008)

Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets. - Alberto Fernández 001; Francisco José Berlanga; María José del Jesus; Francisco Herrera (IFSA/EUSFLAT Conf., 2009)

A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets. - Pedro Villar; Alberto Fernández 001; Francisco Herrera (FUZZ-IEEE, 2009)

A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets. - José Antonio Sanz 001; Alberto Fernández 001; Humberto Bustince Sola; Francisco Herrera (HAIS, 2009)

Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool. - Alberto Fernández 001; Julián Luengo; Joaquín Derrac; Jesús Alcalá-Fdez; Francisco Herrera (IDEAL, 2009)

Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5. - Julián Luengo; Alberto Fernández 001; Salvador García 001; Francisco Herrera (ISDA, 2009)

Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference System. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (IWANN (1), 2009)

A Preliminar Analysis of CO2RBFN in Imbalanced Problems. - M. Dolores Pérez-Godoy; Antonio Jesús Rivera Rivas; Alberto Fernández 001; María José del Jesus; Francisco Herrera (IWANN (1), 2009)

Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems. - Salvador García 001; Alberto Fernández 001; Francisco Herrera (Appl. Soft Comput., 2009)

On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (Expert Syst. Appl., 2009)

Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (Int. J. Approx. Reason., 2009)

A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability. - Salvador García 001; Alberto Fernández 001; Julián Luengo; Francisco Herrera (Soft Comput., 2009)

A genetic algorithm for tuning fuzzy rule-based classification systems with Interval-Valued Fuzzy Sets. - José Antonio Sanz 001; Alberto Fernández 001; Humberto Bustince Sola; Francisco Herrera (FUZZ-IEEE, 2010)

Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (GEFS, 2010)

Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (IPMU, 2010)

A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets. - Pedro Villar; Alberto Fernández 001; Francisco Herrera (IPMU (1), 2010)

A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets. - Victoria López; Alberto Fernández 001; Francisco Herrera (ISDA, 2010)

Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations. - Alberto Fernández 001; María Calderón; Edurne Barrenechea Tartas; Humberto Bustince Sola; Francisco Herrera (Fuzzy Sets Syst., 2010)

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (Inf. Sci., 2010)

Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. - Salvador García 001; Alberto Fernández 001; Julián Luengo; Francisco Herrera (Inf. Sci., 2010)

Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning. - José Antonio Sanz 001; Alberto Fernández 001; Humberto Bustince Sola; Francisco Herrera (Inf. Sci., 2010)

Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets. - M. Dolores Pérez-Godoy; Alberto Fernández 001; Antonio Jesús Rivera Rivas; María José del Jesus (Pattern Recognit. Lett., 2010)

Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study. - Alberto Fernández 001; Salvador García 001; Julián Luengo; Ester Bernadó-Mansilla; Francisco Herrera (IEEE Trans. Evol. Comput., 2010)

Construction of Interval-Valued Fuzzy Preference Relations Using Ignorance Functions: Interval-Valued Non Dominance Criterion. - Edurne Barrenechea; Alberto Fernández 001; Francisco Herrera; Humberto Bustince (Eurofuse, 2011)

On the cooperation of interval-valued fuzzy sets and genetic tuning to improve the performance of fuzzy decision trees. - José Antonio Sanz 001; Humberto Bustince Sola; Alberto Fernández 001; Francisco Herrera (FUZZ-IEEE, 2011)

Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets. - Pedro Villar; Alberto Fernández 001; Francisco Herrera (FUZZ-IEEE, 2011)

Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution. - Alberto Fernández 001; Salvador García 001; Francisco Herrera (HAIS (1), 2011)

A case study on medical diagnosis of cardiovascular diseases using a Genetic Algorithm for Tuning Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets. - José Antonio Sanz 001; Miguel Pagola; Humberto Bustince; Antonio Brugos; Alberto Fernández 001; Francisco Herrera (T2FUZZ, 2011)

A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position. - José Antonio Sanz 001; Alberto Fernández 001; Humberto Bustince Sola; Francisco Herrera (Int. J. Approx. Reason., 2011)

KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. - Jesús Alcalá-Fdez; Alberto Fernández 001; Julián Luengo; Joaquín Derrac; Salvador García 001 (J. Multiple Valued Log. Soft Comput., 2011)

An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea Tartas; Humberto Bustince Sola; Francisco Herrera (Pattern Recognit., 2011)

Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling. - Julián Luengo; Alberto Fernández 001; Salvador García 001; Francisco Herrera (Soft Comput., 2011)

Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations. - Victoria López; Alberto Fernández 001; María José del Jesus; Francisco Herrera (ICPRAM (2), 2012)

An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing. - Alberto Fernández 001; Sara del Río; Francisco Herrera; José Manuel Benítez 001 (KMO, 2012)

Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics. - Victoria López; Alberto Fernández 001; Jose G. Moreno-Torres; Francisco Herrera (Expert Syst. Appl., 2012)

Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets. - Pedro Villar; Alberto Fernández 001; Ramón Alberto Carrasco; Francisco Herrera (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2012)

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea Tartas; Humberto Bustince Sola; Francisco Herrera (IEEE Trans. Syst. Man Cybern. Part C, 2012)

Linguistic Fuzzy Rules in Data Mining: Follow-Up Mamdani Fuzzy Modeling Principle. - Alberto Fernández 001; Francisco Herrera (Combining Experimentation and Theory, 2012)

Addressing covariate shift for Genetic Fuzzy Systems classifiers: A case of study with FARC-HD for imbalanced datasets. - Victoria López; Alberto Fernández 001; Francisco Herrera (FUZZ-IEEE, 2013)

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics. - Victoria López; Alberto Fernández 001; Salvador García 001; Vasile Palade; Francisco Herrera (Inf. Sci., 2013)

Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches. - Alberto Fernández 001; Victoria López; Mikel Galar; María José del Jesus; Francisco Herrera (Knowl. Based Syst., 2013)

A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets. - Victoria López; Alberto Fernández 001; María José del Jesus; Francisco Herrera (Knowl. Based Syst., 2013)

EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea Tartas; Francisco Herrera (Pattern Recognit., 2013)

Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea Tartas; Humberto Bustince Sola; Francisco Herrera (Pattern Recognit., 2013)

IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection. - José Antonio Sanz 001; Alberto Fernández 001; Humberto Bustince; Francisco Herrera (IEEE Trans. Fuzzy Syst., 2013)

Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions. - Mikel Galar; Edurne Barrenechea Tartas; Alberto Fernández 001; Francisco Herrera (FUSION, 2014)

E-learning and educational data mining in cloud computing: an overview. - Alberto Fernández 001; Daniel Peralta; José Manuel Benítez 001; Francisco Herrera (Int. J. Learn. Technol., 2014)

Empowering difficult classes with a similarity-based aggregation in multi-class classification problems. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea; Francisco Herrera (Inf. Sci., 2014)

On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed. - Victoria López; Alberto Fernández 001; Francisco Herrera (Inf. Sci., 2014)

Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks. - Alberto Fernández 001; Sara del Río; Victoria López; Abdullah Bawakid; María José del Jesus; José Manuel Benítez 001; Francisco Herrera (WIREs Data Mining Knowl. Discov., 2014)

New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea; Humberto Bustince; Francisco Herrera (CORES, 2015)

On the Combination of Pairwise and Granularity Learning for Improving Fuzzy Rule-Based Classification Systems: GL-FARCHD-OVO. - Pedro Villar; Alberto Fernández 001; Francisco Herrera (CORES, 2015)

Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection. - Alberto Fernández 001; Mikel Galar; José Antonio Sanz 001; Humberto Bustince; Francisco Herrera (IFSA-EUSFLAT, 2015)

On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm. - Alberto Fernández 001; Mikel Galar; José Antonio Sanz 001; Humberto Bustince; Oscar Cordón; Francisco Herrera (FUZZ-IEEE, 2015)

Improving the OVO performance in Fuzzy Rule-Based Classification Systems by the genetic learning of the granularity level. - Pedro Villar; Alberto Fernández 001; Rosana Montes; Ana Maria Sánchez; Francisco Herrera (FUZZ-IEEE, 2015)

Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection. - Alberto Fernández 001; María José del Jesus; Francisco Herrera (IDEAL, 2015)

On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems. - Salma Elhag; Alberto Fernández 001; Abdullah Bawakid; Saleh Alshomrani; Francisco Herrera (Expert Syst. Appl., 2015)

A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets. - Saleh Alshomrani; Abdullah Bawakid; Seong-O Shim; Alberto Fernández 001; Francisco Herrera (Knowl. Based Syst., 2015)

Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges. - Alberto Fernández 001; Victoria López; María José del Jesus; Francisco Herrera (Knowl. Based Syst., 2015)

DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea; Francisco Herrera (Pattern Recognit., 2015)

Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$-Dimensional Overlap Functions and Decomposition Strategies. - Mikel Elkano; Mikel Galar; José Antonio Sanz 001; Alberto Fernández 001; Edurne Barrenechea Tartas; Francisco Herrera; Humberto Bustince (IEEE Trans. Fuzzy Syst., 2015)

Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification. - Alberto Fernández 001; Francisco Herrera (Fuzzy Logic and Information Fusion, 2016)

A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification. - Alberto Fernández 001; Sara del Río; Francisco Herrera (FUZZ-IEEE, 2016)

Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC). - Alberto Fernández 001; Mikel Elkano; Mikel Galar; José Antonio Sanz 001; Saleh Alshomrani; Humberto Bustince; Francisco Herrera (Int. J. Approx. Reason., 2016)

A View on Fuzzy Systems for Big Data: Progress and Opportunities. - Alberto Fernández 001; Cristóbal J. Carmona; María José del Jesus; Francisco Herrera (Int. J. Comput. Intell. Syst., 2016)

Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea; Humberto Bustince; Francisco Herrera (Inf. Sci., 2016)

Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems. - Alberto Fernández 001; Eva Almansa; Francisco Herrera (FUZZ-IEEE, 2017)

A Review of Distributed Data Models for Learning. - Miguel Ángel Rodríguez; Alberto Fernández 001; Antonio Peregrín; Francisco Herrera (HAIS, 2017)

Fuzzy rule based classification systems for big data with MapReduce: granularity analysis. - Alberto Fernández 001; Sara del Río; Abdullah Bawakid; Francisco Herrera (Adv. Data Anal. Classif., 2017)

Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications? - Alberto Fernández 001; Abdulrahman H. Altalhi; Saleh Alshomrani; Francisco Herrera (Int. J. Comput. Intell. Syst., 2017)

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. - Isaac Triguero; Sergio González; Jose M. Moyano; Salvador García 001; Jesús Alcalá-Fdez; Julián Luengo; Alberto Fernández 001; María José del Jesus; Luciano Sánchez; Francisco Herrera (Int. J. Comput. Intell. Syst., 2017)

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. - Alberto Fernández 001; Cristóbal J. Carmona; María José del Jesus; Francisco Herrera (Int. J. Neural Syst., 2017)

NMC: nearest matrix classification - A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem. - Mikel Galar; Alberto Fernández 001; Edurne Barrenechea; Humberto Bustince; Francisco Herrera (Inf. Fusion, 2017)

Learning from Imbalanced Data Sets - Alberto Fernández 001; Salvador García 001; Mikel Galar; Ronaldo C. Prati; Bartosz Krawczyk; Francisco Herrera (Springer, 2018)

Improving Fuzzy Rule Based Classification Systems in Big Data via Support-based Filtering. - Luis Íñiguez; Mikel Galar; Alberto Fernández 001 (FUZZ-IEEE, 2018)

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers. - Deborah Galpert; Alberto Fernández 001; Francisco Herrera; Agostinho Antunes; Reinaldo Molina Ruiz; Guillermín Agüero-Chapín (BMC Bioinform., 2018)

Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce. - Sergio Ramírez-Gallego; Alberto Fernández 001; Salvador García 001; Min Chen 003; Francisco Herrera (Inf. Fusion, 2018)

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary. - Alberto Fernández 001; Salvador García 001; Francisco Herrera; Nitesh V. Chawla (J. Artif. Intell. Res., 2018)

SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data. - María José Basgall; Waldo Hasperué; Marcelo R. Naiouf; Alberto Fernández 001; Francisco Herrera (J. Comput. Sci. Technol., 2018)

Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach. - Sarah Vluymans; Alberto Fernández 001; Yvan Saeys; Chris Cornelis; Francisco Herrera (Knowl. Inf. Syst., 2018)

Imbalance: Oversampling algorithms for imbalanced classification in R. - Ignacio Cordón; Salvador García 001; Alberto Fernández 001; Francisco Herrera (Knowl. Based Syst., 2018)

On the Need of Interpretability for Biomedical Applications: Using Fuzzy Models for Lung Cancer Prediction with Liquid Biopsy. - Nicolas Potie; Stavros Giannoukakos; Michael Hackenberg; Alberto Fernández 001 (FUZZ-IEEE, 2019)

An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing. - María José Basgall; Waldo Hasperué; Marcelo R. Naiouf; Alberto Fernández 001; Francisco Herrera (JCC&BD, 2019)

Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? - Alberto Fernández 001; Francisco Herrera; Oscar Cordón; María José del Jesus; Francesco Marcelloni (IEEE Comput. Intell. Mag., 2019)

Guest Editorial: Computational Intelligence for Big Data Analytics. - Alberto Fernández 001; Isaac Triguero; Mikel Galar; Francisco Herrera (Cogn. Comput., 2019)

A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems. - Salma Elhag; Alberto Fernández 001; Abdulrahman H. Altalhi; Saleh Alshomrani; Francisco Herrera (Soft Comput., 2019)

A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity. - Javier Cózar; Alberto Fernández 001; Francisco Herrera; José A. Gámez 001 (IEEE Trans. Fuzzy Syst., 2019)

Chi-BD-DRF: Design of Scalable Fuzzy Classifiers for Big Data via A Dynamic Rule Filtering Approach. - Fatemeh Aghaeipoor; Mohammad Masoud Javidi; Isaac Triguero; Alberto Fernández 001 (FUZZ-IEEE, 2020)

HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules. - José Ramón Trillo; Alberto Fernández 001; Francisco Herrera (FUZZ-IEEE, 2020)

Applying Feature Selection to Improve Predictive Performance and Explainability in Lung Cancer Detection with Soft Computing. - Nicolas Potie; Stavros Giannoukakos; Michael Hackenberg; Alberto Fernández 001 (HICSS, 2020)

Discussion on Vuttipittayamongkol, P. and Elyan, E., Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson's Disease. - Alberto Fernández 001 (Int. J. Neural Syst., 2020)

Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies. - J. A. Fdez-Sánchez; José Daniel Pascual-Triana; Alberto Fernández 001; Francisco Herrera (Neurocomputing, 2021)

Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect. - José Daniel Pascual-Triana; David Charte; Marta Andrés Arroyo; Alberto Fernández 001; Francisco Herrera (Knowl. Inf. Syst., 2021)

SOUL: Scala Oversampling and Undersampling Library for imbalance classification. - Néstor Rodríguez; David López; Alberto Fernández 001; Salvador García 001; Francisco Herrera (SoftwareX, 2021)

On the joint-effect of class imbalance and overlap: a critical review. - Miriam Seoane Santos; Pedro Henriques Abreu; Nathalie Japkowicz; Alberto Fernández 001; Carlos Soares; Szymon Wilk; João A. M. Santos (Artif. Intell. Rev., 2022)

The impact of heterogeneous distance functions on missing data imputation and classification performance. - Miriam Seoane Santos; Pedro Henriques Abreu; Alberto Fernández 001; Julián Luengo; João A. M. Santos (Eng. Appl. Artif. Intell., 2022)

An efficiency curve for evaluating imbalanced classifiers considering intrinsic data characteristics: Experimental analysis. - Xiangrui Chao; Gang Kou; Yi Peng 001; Alberto Fernández 001 (Inf. Sci., 2022)

FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification. - Sebastián Maldonado; Carla Vairetti; Alberto Fernández 001; Francisco Herrera (Pattern Recognit., 2022)

IFC-BD: An Interpretable Fuzzy Classifier for Boosting Explainable Artificial Intelligence in Big Data. - Fatemeh Aghaeipoor; Mohammad Masoud Javidi; Alberto Fernández 001 (IEEE Trans. Fuzzy Syst., 2022)

A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. - Miriam Seoane Santos; Pedro Henriques Abreu; Nathalie Japkowicz; Alberto Fernández 001; João A. M. Santos (Inf. Fusion, 2023)

Fuzzy Rule-Based Explainer Systems for Deep Neural Networks: From Local Explainability to Global Understanding. - Fatemeh Aghaeipoor; Mohammad Sabokrou; Alberto Fernández 001 (IEEE Trans. Fuzzy Syst., 2023)

A Wearable Eye-Tracking Approach for Early Autism Detection with Machine Learning: Unravelling Challenges and Opportunities. - J. Lopez-Martinez; Purificación Checa; José Manuel Soto-Hidalgo; Isaac Triguero; Alberto Fernández 001 (IJCNN, 2024)

Fair Overlap Number of Balls (Fair-ONB): A Data-Morphology-based Undersampling Method for Bias Reduction. - José Daniel Pascual-Triana; Alberto Fernández 001; Paulo Novais; Francisco Herrera (CoRR, 2024)

Overlap Number of Balls Model-Agnostic CounterFactuals (ONB-MACF): A data-morphology-based counterfactual generation method for trustworthy artificial intelligence. - José Daniel Pascual-Triana; Alberto Fernández 001; Javier Del Ser; Francisco Herrera (Inf. Sci., 2025)