Alberto Fernández

发表

Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, Int. J. Approx. Reason..

EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2013, Pattern Recognit..

Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution

Francisco Herrera, Salvador García, Alberto Fernández, 2011, HAIS.

A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets

Francisco Herrera, Alberto Fernández, Pedro Villar, 2009, 2009 IEEE International Conference on Fuzzy Systems.

Chi-BD-DRF: Design of Scalable Fuzzy Classifiers for Big Data via A Dynamic Rule Filtering Approach

Alberto Fernández, Mohammad Masoud Javidi, Isaac Triguero, 2020, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling

Francisco Herrera, Salvador García, Alberto Fernández, 2011, Soft Comput..

Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems

Francisco Herrera, Alberto Fernández, Eva Almansa, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing

Francisco Herrera, Alberto Fernández, Marcelo R. Naiouf, 2019, JCC&BD.

Fuzzy rule based classification systems for big data with MapReduce: granularity analysis

Francisco Herrera, Alberto Fernández, Sara del Río, 2017, Adv. Data Anal. Classif..

Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference System

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, IWANN.

New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, CORES.

A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets

Francisco Herrera, Alberto Fernández, Pedro Villar, 2010, IPMU.

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2017, Int. J. Neural Syst..

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

Francisco Herrera, Salvador García, Alberto Fernández, 2013, Inf. Sci..

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

María José del Jesús, Francisco Herrera, Jesús Alcalá-Fdez, 2017, Int. J. Comput. Intell. Syst..

Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection

María José del Jesús, Francisco Herrera, Alberto Fernández, 2015, IDEAL.

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

Francisco Herrera, Nitesh V. Chawla, Salvador García, 2018, J. Artif. Intell. Res..

DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2015, Pattern Recognit..

Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

Francisco Herrera, Salvador García, Alberto Fernández, 2010, Inf. Sci..

A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2013, Knowl. Based Syst..

Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks

María José del Jesús, Francisco Herrera, Alberto Fernández, 2014, WIREs Data Mining Knowl. Discov..

A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets

María José del Jesús, Francisco Herrera, Salvador García, 2007, IWANN.

A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets

Francisco Herrera, Alberto Fernández, Saleh Alshomrani, 2015, Knowl. Based Syst..

An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing

Francisco Herrera, Alberto Fernández, José Manuel Benítez, 2012, KMO.

On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm

Francisco Herrera, Humberto Bustince, Oscar Cordón, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

Francisco Herrera, Salvador García, Alberto Fernández, 2009, Soft Comput..

A genetic algorithm for tuning fuzzy rule-based classification systems with Interval-Valued Fuzzy Sets

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2010, International Conference on Fuzzy Systems.

Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2014, 17th International Conference on Information Fusion (FUSION).

An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets

María José del Jesús, Francisco Herrera, Salvador García, 2007, WILF.

On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems

Francisco Herrera, Alberto Fernández, Saleh Alshomrani, 2015, Expert Syst. Appl..

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, Alberto Fernández, 2020, Int. J. Neural Syst..

Construction of Interval-Valued Fuzzy Preference Relations Using Ignorance Functions: Interval-Valued Non Dominance Criterion

Francisco Herrera, Humberto Bustince, Edurne Barrenechea Tartas, 2011, Eurofuse.

IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2013, IEEE Transactions on Fuzzy Systems.

E-learning and educational data mining in cloud computing: an overview

Francisco Herrera, Alberto Fernández, Daniel Peralta, 2014, Int. J. Learn. Technol..

A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2011, Int. J. Approx. Reason..

A Short Study on the Use of Genetic 2-Tuples Tuning for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems

Francisco Herrera, Abdulrahman H. Altalhi, Alberto Fernández, 2019, Soft Comput..

Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations

María José del Jesús, Francisco Herrera, Alberto Fernández, 2012, ICPRAM.

Learning from Imbalanced Data Sets

Francisco Herrera, Mikel Galar, Salvador García, 2018, Springer International Publishing.

A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

María José del Jesús, Francisco Herrera, Salvador García, 2008, Fuzzy Sets Syst..

Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC)

Francisco Herrera, Humberto Bustince, Mikel Galar, 2016, Int. J. Approx. Reason..

Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification

Francisco Herrera, Alberto Fernández, F. Herrera, 2016, Fuzzy Logic and Information Fusion.

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

Francisco Herrera, Humberto Bustince, Mikel Galar, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5

Francisco Herrera, Salvador García, Alberto Fernández, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

NMC: nearest matrix classification - A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem

Francisco Herrera, Humberto Bustince, Mikel Galar, 2017, Inf. Fusion.

Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, 2010 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity

Francisco Herrera, José A. Gámez, Alberto Fernández, 2019, IEEE Transactions on Fuzzy Systems.

A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets

Francisco Herrera, Alberto Fernández, Victoria López, 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

Improving Fuzzy Rule Based Classification Systems in Big Data via Support-based Filtering

Mikel Galar, Alberto Fernández, Luis Iniguez, 2018, 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets

Francisco Herrera, Humberto Bustince, Mikel Galar, 2016, Inf. Sci..

On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed

Francisco Herrera, Alberto Fernández, Victoria López, 2014, Inf. Sci..

Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2010, Inf. Sci..

Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2018, Knowledge and Information Systems.

A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2009, HAIS.

Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$-Dimensional Overlap Functions and Decomposition Strategies

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, IEEE Transactions on Fuzzy Systems.

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, Inf. Sci..

Preprocessing Algorithms for Imbalanced Datasets [R package imbalance version 1.0.2.1]

Francisco Herrera, Salvador García, Alberto Fernández, 2020 .

An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes

Francisco Herrera, Humberto Bustince, Mikel Galar, 2011, Pattern Recognit..

Empowering difficult classes with a similarity-based aggregation in multi-class classification problems

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2014, Inf. Sci..

Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges

María José del Jesús, Francisco Herrera, Alberto Fernández, 2015, Knowl. Based Syst..

Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, IFSA/EUSFLAT Conf..

Linguistic Fuzzy Rules in Data Mining: Follow-Up Mamdani Fuzzy Modeling Principle

Francisco Herrera, Alberto Fernández, F. Herrera, 2012, Combining Experimentation and Theory.

On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, Expert Syst. Appl..

On the Combination of Pairwise and Granularity Learning for Improving Fuzzy Rule-Based Classification Systems: GL-FARCHD-OVO

Francisco Herrera, Alberto Fernández, Pedro Villar, 2015, CORES.

Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers

Francisco Herrera, Humberto Bustince, Mikel Galar, 2013, Pattern Recognit..

Guest Editorial: Computational Intelligence for Big Data Analytics

Francisco Herrera, Mikel Galar, Alberto Fernández, 2019, Cognitive Computation.

A View on Fuzzy Systems for Big Data: Progress and Opportunities

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2016, Int. J. Comput. Intell. Syst..

Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems

Francisco Herrera, Salvador García, Alberto Fernández, 2009, Appl. Soft Comput..

A Review of Distributed Data Models for Learning

Francisco Herrera, Alberto Fernández, Antonio Peregrín, 2017, HAIS.

Imbalance: Oversampling algorithms for imbalanced classification in R

Francisco Herrera, Salvador García, Alberto Fernández, 2018, Knowl. Based Syst..

Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?

Francisco Herrera, Abdulrahman H. Altalhi, Alberto Fernández, 2017, Int. J. Comput. Intell. Syst..

A Proposal of Evolutionary Prototype Selection for Class Imbalance Problems

Francisco Herrera, José Ramón Cano, Salvador García, 2006, IDEAL.

Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets

Francisco Herrera, Alberto Fernández, Ramón Alberto Carrasco, 2012, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, IPMU.

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

Francisco Herrera, Humberto Bustince, Miguel Pagola, 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

Addressing covariate shift for Genetic Fuzzy Systems classifiers: A case of study with FARC-HD for imbalanced datasets

Francisco Herrera, Alberto Fernández, Victoria López, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

María José del Jesús, Francisco Herrera, Oscar Cordón, 2019, IEEE Computational Intelligence Magazine.

A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification

Francisco Herrera, Alberto Fernández, Sara del Río, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations

Francisco Herrera, Humberto Bustince, Edurne Barrenechea Tartas, 2010, Fuzzy Sets Syst..

Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, IFSA-EUSFLAT.

Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies

Alberto Fernández, J. A. Fdez-Sánchez, José Daniel Pascual-Triana, 2021, Neurocomputing.

SOUL: Scala Oversampling and Undersampling Library for imbalance classification

Salvador García, Alberto Fernández, Francisco Herrera, 2021, SoftwareX.

FDR2-BD: A Fast Data Reduction Recommendation Tool for Tabular Big Data Classification Problems

Alberto Fernández, Marcelo Naiouf, María José Basgall, 2021, Electronics.

On the Usefulness of Fuzzy Rule Based Systems Based on Hierarchical Linguistic Fuzzy Partitions

Francisco Herrera, Alberto Fernández, María José del Jesus, 2011 .

Enhancing Fuzzy Rule Based Systems in Multi-Classification Using Pairwise Coupling with Preference Relations

Alberto Fernández, Alberto Fernández, 2009 .

A First Study on the Use of Fuzzy Rule Based Classification Systems for Problems with Imbalanced Data Sets ?

Alberto Fernández, S. García, Alberto Fernández, 2006 .

Aggregation schemes for binarization techniques . Methods ’ description

Francisco Herrera, Humberto Bustince, Mikel Galar, 2010 .