Alberto Fernández
Orcid: 0000-0002-6480-8434Affiliations:
- University of Granada, Department of Computer Science and Artificial Intelligence, Spain
- University of Jaén, Department of Computer Science, Spain (former)
According to our database1,
Alberto Fernández
authored at least 102 papers
between 2006 and 2023.
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Bibliography
2023
Fuzzy Rule-Based Explainer Systems for Deep Neural Networks: From Local Explainability to Global Understanding.
IEEE Trans. Fuzzy Syst., September, 2023
A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research.
Inf. Fusion, 2023
2022
IFC-BD: An Interpretable Fuzzy Classifier for Boosting Explainable Artificial Intelligence in Big Data.
IEEE Trans. Fuzzy Syst., 2022
Pattern Recognit., 2022
The impact of heterogeneous distance functions on missing data imputation and classification performance.
Eng. Appl. Artif. Intell., 2022
Artif. Intell. Rev., 2022
2021
SoftwareX, 2021
Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect.
Knowl. Inf. Syst., 2021
Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies.
Neurocomputing, 2021
2020
HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules.
Proceedings of the 29th IEEE International Conference on Fuzzy Systems, 2020
Chi-BD-DRF: Design of Scalable Fuzzy Classifiers for Big Data via A Dynamic Rule Filtering Approach.
Proceedings of the 29th IEEE International Conference on Fuzzy Systems, 2020
2019
A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity.
IEEE Trans. Fuzzy Syst., 2019
A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems.
Soft Comput., 2019
Cogn. Comput., 2019
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?
IEEE Comput. Intell. Mag., 2019
An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing.
Proceedings of the 7th Conference on Cloud Computing & Big Data, 2019
2018
Knowl. Based Syst., 2018
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach.
Knowl. Inf. Syst., 2018
SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data.
J. Comput. Sci. Technol., 2018
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary.
J. Artif. Intell. Res., 2018
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce.
Inf. Fusion, 2018
Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.
BMC Bioinform., 2018
Improving Fuzzy Rule Based Classification Systems in Big Data via Support-based Filtering.
Proceedings of the 2018 IEEE International Conference on Fuzzy Systems, 2018
2017
NMC: nearest matrix classification - A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem.
Inf. Fusion, 2017
A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.
Int. J. Neural Syst., 2017
Int. J. Comput. Intell. Syst., 2017
Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?
Int. J. Comput. Intell. Syst., 2017
Fuzzy rule based classification systems for big data with MapReduce: granularity analysis.
Adv. Data Anal. Classif., 2017
Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017
Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems.
Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017
2016
Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets.
Inf. Sci., 2016
Int. J. Comput. Intell. Syst., 2016
Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC).
Int. J. Approx. Reason., 2016
A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification.
Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016
Proceedings of the Fuzzy Logic and Information Fusion, 2016
2015
Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$-Dimensional Overlap Functions and Decomposition Strategies.
IEEE Trans. Fuzzy Syst., 2015
DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems.
Pattern Recognit., 2015
Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges.
Knowl. Based Syst., 2015
A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets.
Knowl. Based Syst., 2015
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems.
Expert Syst. Appl., 2015
Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2015, 2015
Improving the OVO performance in Fuzzy Rule-Based Classification Systems by the genetic learning of the granularity level.
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015
On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm.
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015
Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection.
Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15), 2015
On the Combination of Pairwise and Granularity Learning for Improving Fuzzy Rule-Based Classification Systems: GL-FARCHD-OVO.
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, 2015
New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets.
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, 2015
2014
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks.
WIREs Data Mining Knowl. Discov., 2014
On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed.
Inf. Sci., 2014
Empowering difficult classes with a similarity-based aggregation in multi-class classification problems.
Inf. Sci., 2014
Int. J. Learn. Technol., 2014
Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions.
Proceedings of the 17th International Conference on Information Fusion, 2014
2013
IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection.
IEEE Trans. Fuzzy Syst., 2013
Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers.
Pattern Recognit., 2013
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling.
Pattern Recognit., 2013
A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets.
Knowl. Based Syst., 2013
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches.
Knowl. Based Syst., 2013
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics.
Inf. Sci., 2013
Addressing covariate shift for Genetic Fuzzy Systems classifiers: A case of study with FARC-HD for imbalanced datasets.
Proceedings of the FUZZ-IEEE 2013, 2013
2012
Proceedings of the Combining Experimentation and Theory - A Hommage to Abe Mamdani, 2012
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches.
IEEE Trans. Syst. Man Cybern. Part C, 2012
Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2012
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics.
Expert Syst. Appl., 2012
An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing.
Proceedings of the 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing, 2012
Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations.
Proceedings of the ICPRAM 2012, 2012
2011
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling.
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.
Pattern Recognit., 2011
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework.
J. Multiple Valued Log. Soft Comput., 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.
Int. J. Approx. Reason., 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.
Proceedings of the 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems, 2011
Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution.
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011
Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets.
Proceedings of the FUZZ-IEEE 2011, 2011
On the cooperation of interval-valued fuzzy sets and genetic tuning to improve the performance of fuzzy decision trees.
Proceedings of the FUZZ-IEEE 2011, 2011
Construction of Interval-Valued Fuzzy Preference Relations Using Ignorance Functions: Interval-Valued Non Dominance Criterion.
Proceedings of the Eurofuse 2011, 2011
2010
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study.
IEEE Trans. Evol. Comput., 2010
Analysis of an evolutionary RBFN design algorithm, CO<sup>2</sup>RBFN, for imbalanced data sets.
Pattern Recognit. Lett., 2010
Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning.
Inf. Sci., 2010
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power.
Inf. Sci., 2010
On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets.
Inf. Sci., 2010
Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations.
Fuzzy Sets Syst., 2010
A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets.
Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010
A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods, 2010
Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning.
Proceedings of the Computational Intelligence for Knowledge-Based Systems Design, 2010
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection.
Proceedings of the 4th IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems, 2010
A genetic algorithm for tuning fuzzy rule-based classification systems with Interval-Valued Fuzzy Sets.
Proceedings of the FUZZ-IEEE 2010, 2010
2009
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability.
Soft Comput., 2009
Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets.
Int. J. Approx. Reason., 2009
On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets.
Expert Syst. Appl., 2009
Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems.
Appl. Soft Comput., 2009
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009
Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference System.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009
Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009
Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009
A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009
A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets.
Proceedings of the FUZZ-IEEE 2009, 2009
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets.
Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, 2009
2008
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets.
Fuzzy Sets Syst., 2008
A Short Study on the Use of Genetic 2-Tuples Tuning for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008
Proceedings of the 3rd International Workshop on Genetic and Evolving Systems, 2008
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.
Proceedings of the Applications of Fuzzy Sets Theory, 2007
A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets.
Proceedings of the Computational and Ambient Intelligence, 2007
2006
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006