Alberto Fernández

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 37

Top Venues

FUZZ-IEEE

IEEE Trans. Fuzzy Syst.

Int. J. Comput. Intell. Syst.

Inf. Sci.

Publications

José Daniel Pascual-Triana, Alberto Fernández, Paulo Novais, Francisco Herrera
Fair Overlap Number of Balls (Fair-ONB): A Data-Morphology-based Undersampling Method for Bias Reduction. CoRR (2024)
José Daniel Pascual-Triana, Alberto Fernández, Javier Del Ser, Francisco Herrera
Overlap Number of Balls Model-Agnostic CounterFactuals (ONB-MACF): A Data-Morphology-based Counterfactual Generation Method for Trustworthy Artificial Intelligence. CoRR (2024)
Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, João A. M. Santos
A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. Inf. Fusion 89 (2023)
Fatemeh Aghaeipoor, Mohammad Sabokrou, Alberto Fernández
Fuzzy Rule-Based Explainer Systems for Deep Neural Networks: From Local Explainability to Global Understanding. IEEE Trans. Fuzzy Syst. 31 (9) (2023)
Sebastián Maldonado, Carla Vairetti, Alberto Fernández, Francisco Herrera
FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification. Pattern Recognit. 124 (2022)
Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, Carlos Soares, Szymon Wilk, João A. M. Santos
On the joint-effect of class imbalance and overlap: a critical review. Artif. Intell. Rev. 55 (8) (2022)
Miriam Seoane Santos, Pedro Henriques Abreu, Alberto Fernández, Julián Luengo, João A. M. Santos
The impact of heterogeneous distance functions on missing data imputation and classification performance. Eng. Appl. Artif. Intell. 111 (2022)
Fatemeh Aghaeipoor, Mohammad Masoud Javidi, Alberto Fernández
IFC-BD: An Interpretable Fuzzy Classifier for Boosting Explainable Artificial Intelligence in Big Data. IEEE Trans. Fuzzy Syst. 30 (3) (2022)
Néstor Rodríguez, David López, Alberto Fernández, Salvador García, Francisco Herrera
SOUL: Scala Oversampling and Undersampling Library for imbalance classification. SoftwareX 15 (2021)
José Daniel Pascual-Triana, David Charte, Marta Andrés Arroyo, Alberto Fernández, Francisco Herrera
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. 63 (7) (2021)
J. A. Fdez-Sánchez, José Daniel Pascual-Triana, Alberto Fernández, Francisco Herrera
Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies. Neurocomputing 463 (2021)
José Daniel Pascual-Triana, David Charte, Marta Andrés Arroyo, Alberto Fernández, Francisco Herrera
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect. CoRR (2020)
Fatemeh Aghaeipoor, Mohammad Masoud Javidi, Isaac Triguero, Alberto Fernández
Chi-BD-DRF: Design of Scalable Fuzzy Classifiers for Big Data via A Dynamic Rule Filtering Approach. FUZZ-IEEE (2020)
Salma Elhag, Alberto Fernández, Abdulrahman H. Altalhi, Saleh Alshomrani, Francisco Herrera
A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems. Soft Comput. 23 (4) (2019)
Javier Cózar, Alberto Fernández, Francisco Herrera, José A. Gámez
A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity. IEEE Trans. Fuzzy Syst. 27 (4) (2019)
Alberto Fernández, Francisco Herrera, Oscar Cordón, María José del Jesus, Francesco Marcelloni
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? IEEE Comput. Intell. Mag. 14 (1) (2019)
Alberto Fernández, Isaac Triguero, Mikel Galar, Francisco Herrera
Guest Editorial: Computational Intelligence for Big Data Analytics. Cogn. Comput. 11 (3) (2019)
María José Basgall, Waldo Hasperué, Marcelo R. Naiouf, Alberto Fernández, Francisco Herrera
An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing. JCC&BD (2019)
María José Basgall, Waldo Hasperué, Marcelo R. Naiouf, Alberto Fernández, Francisco Herrera
SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data. J. Comput. Sci. Technol. 18 (03) (2018)
Ignacio Cordón, Salvador García, Alberto Fernández, Francisco Herrera
Imbalance: Oversampling algorithms for imbalanced classification in R. Knowl. Based Syst. 161 (2018)
Alberto Fernández, Salvador García, Francisco Herrera, Nitesh V. Chawla
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary. J. Artif. Intell. Res. 61 (2018)
Sarah Vluymans, Alberto Fernández, Yvan Saeys, Chris Cornelis, Francisco Herrera
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach. Knowl. Inf. Syst. 56 (1) (2018)
Sergio Ramírez-Gallego, Alberto Fernández, Salvador García, Min Chen, Francisco Herrera
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce. Inf. Fusion 42 (2018)
Luis Íñiguez, Mikel Galar, Alberto Fernández
Improving Fuzzy Rule Based Classification Systems in Big Data via Support-based Filtering. FUZZ-IEEE (2018)
Deborah Galpert, Alberto Fernández, Francisco Herrera, Agostinho Antunes, Reinaldo Molina Ruiz, Guillermín Agüero-Chapín
Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers. BMC Bioinform. 19 (1) (2018)
Alberto Fernández, Eva Almansa, Francisco Herrera
Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems. FUZZ-IEEE (2017)
Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, María José del Jesus, Luciano Sánchez, Francisco Herrera
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. Int. J. Comput. Intell. Syst. 10 (1) (2017)
Miguel Ángel Rodríguez, Alberto Fernández, Antonio Peregrín, Francisco Herrera
A Review of Distributed Data Models for Learning. HAIS (2017)
Alberto Fernández, Sara del Río, Abdullah Bawakid, Francisco Herrera
Fuzzy rule based classification systems for big data with MapReduce: granularity analysis. Adv. Data Anal. Classif. 11 (4) (2017)
Alberto Fernández, Cristóbal J. Carmona, María José del Jesus, Francisco Herrera
A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. Int. J. Neural Syst. 27 (6) (2017)
Mikel Galar, Alberto Fernández, Edurne Barrenechea, Humberto Bustince, Francisco Herrera
NMC: nearest matrix classification - A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem. Inf. Fusion 36 (2017)
Alberto Fernández, Abdulrahman H. Altalhi, Saleh Alshomrani, Francisco Herrera
Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications? Int. J. Comput. Intell. Syst. 10 (1) (2017)
Alberto Fernández, Sara del Río, Francisco Herrera
A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification. FUZZ-IEEE (2016)
Alberto Fernández, Mikel Elkano, Mikel Galar, José Antonio Sanz, Saleh Alshomrani, Humberto Bustince, Francisco Herrera
Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC). Int. J. Approx. Reason. 73 (2016)
Alberto Fernández, Cristóbal J. Carmona, María José del Jesus, Francisco Herrera
A View on Fuzzy Systems for Big Data: Progress and Opportunities. Int. J. Comput. Intell. Syst. 9 (sup1) (2016)
Mikel Galar, Alberto Fernández, Edurne Barrenechea, Humberto Bustince, Francisco Herrera
Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets. Inf. Sci. 354 (2016)
Alberto Fernández, Francisco Herrera
Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification. Fuzzy Logic and Information Fusion (2016)
Mikel Galar, Alberto Fernández, Edurne Barrenechea, Humberto Bustince, Francisco Herrera
New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets. CORES (2015)
Mikel Galar, Alberto Fernández, Edurne Barrenechea, Francisco Herrera
DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems. Pattern Recognit. 48 (1) (2015)
Alberto Fernández, Victoria López, María José del Jesus, Francisco Herrera
Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges. Knowl. Based Syst. 80 (2015)
Mikel Elkano, Mikel Galar, José Antonio Sanz, Alberto Fernández, Edurne Barrenechea Tartas, Francisco Herrera, Humberto Bustince
Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$-Dimensional Overlap Functions and Decomposition Strategies. IEEE Trans. Fuzzy Syst. 23 (5) (2015)
Salma Elhag, Alberto Fernández, Abdullah Bawakid, Saleh Alshomrani, Francisco Herrera
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems. Expert Syst. Appl. 42 (1) (2015)
Alberto Fernández, Mikel Galar, José Antonio Sanz, Humberto Bustince, Oscar Cordón, Francisco Herrera
On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm. FUZZ-IEEE (2015)
Alberto Fernández, Mikel Galar, José Antonio Sanz, Humberto Bustince, Francisco Herrera
Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection. IFSA-EUSFLAT (2015)
Pedro Villar, Alberto Fernández, Rosana Montes, Ana Maria Sánchez, Francisco Herrera
Improving the OVO performance in Fuzzy Rule-Based Classification Systems by the genetic learning of the granularity level. FUZZ-IEEE (2015)
Alberto Fernández, María José del Jesus, Francisco Herrera
Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection. IDEAL (2015)
Saleh Alshomrani, Abdullah Bawakid, Seong-O Shim, Alberto Fernández, Francisco Herrera
A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets. Knowl. Based Syst. 73 (2015)
Pedro Villar, Alberto Fernández, Francisco Herrera
On the Combination of Pairwise and Granularity Learning for Improving Fuzzy Rule-Based Classification Systems: GL-FARCHD-OVO. CORES (2015)
Mikel Galar, Alberto Fernández, Edurne Barrenechea, Francisco Herrera
Empowering difficult classes with a similarity-based aggregation in multi-class classification problems. Inf. Sci. 264 (2014)
Alberto Fernández, Sara del Río, Victoria López, Abdullah Bawakid, María José del Jesus, José Manuel Benítez, Francisco Herrera
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks. WIREs Data Mining Knowl. Discov. 4 (5) (2014)
Alberto Fernández, Daniel Peralta, José Manuel Benítez, Francisco Herrera
E-learning and educational data mining in cloud computing: an overview. Int. J. Learn. Technol. 9 (1) (2014)
Victoria López, Alberto Fernández, Francisco Herrera
On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed. Inf. Sci. 257 (2014)
Mikel Galar, Edurne Barrenechea Tartas, Alberto Fernández, Francisco Herrera
Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions. FUSION (2014)
Mikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera
Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers. Pattern Recognit. 46 (12) (2013)
Victoria López, Alberto Fernández, Salvador García, Vasile Palade, Francisco Herrera
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics. Inf. Sci. 250 (2013)
Mikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Francisco Herrera
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling. Pattern Recognit. 46 (12) (2013)
José Antonio Sanz, Alberto Fernández, Humberto Bustince, Francisco Herrera
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. 21 (3) (2013)
Victoria López, Alberto Fernández, María José del Jesus, Francisco Herrera
A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets. Knowl. Based Syst. 38 (2013)
Alberto Fernández, Victoria López, Mikel Galar, María José del Jesus, Francisco Herrera
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches. Knowl. Based Syst. 42 (2013)
Victoria López, Alberto Fernández, Francisco Herrera
Addressing covariate shift for Genetic Fuzzy Systems classifiers: A case of study with FARC-HD for imbalanced datasets. FUZZ-IEEE (2013)
Alberto Fernández, Sara del Río, Francisco Herrera, José Manuel Benítez
An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing. KMO (2012)
Victoria López, Alberto Fernández, María José del Jesus, Francisco Herrera
Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations. ICPRAM (2) (2012)
Victoria López, Alberto Fernández, Jose G. Moreno-Torres, Francisco Herrera
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics. Expert Syst. Appl. 39 (7) (2012)
Mikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches. IEEE Trans. Syst. Man Cybern. Part C 42 (4) (2012)
Pedro Villar, Alberto Fernández, Ramón Alberto Carrasco, Francisco Herrera
Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20 (3) (2012)
José Antonio Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera
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. 52 (6) (2011)
Julián Luengo, Alberto Fernández, Salvador García, Francisco Herrera
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling. Soft Comput. 15 (10) (2011)
José Antonio Sanz, Miguel Pagola, Humberto Bustince, Antonio Brugos, Alberto Fernández, Francisco Herrera
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. T2FUZZ (2011)
Jesús Alcalá-Fdez, Alberto Fernández, Julián Luengo, Joaquín Derrac, Salvador García
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. J. Multiple Valued Log. Soft Comput. 17 (2-3) (2011)
Mikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera
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. 44 (8) (2011)
José Antonio Sanz, Humberto Bustince Sola, Alberto Fernández, Francisco Herrera
On the cooperation of interval-valued fuzzy sets and genetic tuning to improve the performance of fuzzy decision trees. FUZZ-IEEE (2011)
Pedro Villar, Alberto Fernández, Francisco Herrera
Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets. FUZZ-IEEE (2011)
Edurne Barrenechea, Alberto Fernández, Francisco Herrera, Humberto Bustince
Construction of Interval-Valued Fuzzy Preference Relations Using Ignorance Functions: Interval-Valued Non Dominance Criterion. Eurofuse (2011)
Alberto Fernández, Salvador García, Francisco Herrera
Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution. HAIS (1) (2011)
Alberto Fernández, Salvador García, Julián Luengo, Ester Bernadó-Mansilla, Francisco Herrera
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study. IEEE Trans. Evol. Comput. 14 (6) (2010)
José Antonio Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera
Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning. Inf. Sci. 180 (19) (2010)
M. Dolores Pérez-Godoy, Alberto Fernández, Antonio Jesús Rivera Rivas, María José del Jesus
RBFN, for imbalanced data sets. Pattern Recognit. Lett. 31 (15) (2010)
Victoria López, Alberto Fernández, Francisco Herrera
A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets. ISDA (2010)
Salvador García, Alberto Fernández, Julián Luengo, Francisco Herrera
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. Inf. Sci. 180 (10) (2010)
Alberto Fernández, María José del Jesus, Francisco Herrera
On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets. Inf. Sci. 180 (8) (2010)
Alberto Fernández, María Calderón, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera
Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations. Fuzzy Sets Syst. 161 (23) (2010)
José Antonio Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera
A genetic algorithm for tuning fuzzy rule-based classification systems with Interval-Valued Fuzzy Sets. FUZZ-IEEE (2010)
Pedro Villar, Alberto Fernández, Francisco Herrera
A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets. IPMU (1) (2010)
Alberto Fernández, María José del Jesus, Francisco Herrera
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection. GEFS (2010)
Alberto Fernández, María José del Jesus, Francisco Herrera
Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning. IPMU (2010)
Salvador García, Alberto Fernández, Julián Luengo, Francisco Herrera
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability. Soft Comput. 13 (10) (2009)
Alberto Fernández, Julián Luengo, Joaquín Derrac, Jesús Alcalá-Fdez, Francisco Herrera
Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool. IDEAL (2009)
M. Dolores Pérez-Godoy, Antonio Jesús Rivera Rivas, Alberto Fernández, María José del Jesus, Francisco Herrera
A Preliminar Analysis of CO2RBFN in Imbalanced Problems. IWANN (1) (2009)
Pedro Villar, Alberto Fernández, Francisco Herrera
A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets. FUZZ-IEEE (2009)
Salvador García, Alberto Fernández, Francisco Herrera
Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems. Appl. Soft Comput. 9 (4) (2009)
Alberto Fernández, María José del Jesus, Francisco Herrera
On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets. Expert Syst. Appl. 36 (6) (2009)
Alberto Fernández, Francisco José Berlanga, María José del Jesus, Francisco Herrera
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets. IFSA/EUSFLAT Conf. (2009)
José Antonio Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera
A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets. HAIS (2009)
Julián Luengo, Alberto Fernández, Salvador García, Francisco Herrera
Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5. ISDA (2009)
Alberto Fernández, María José del Jesus, Francisco Herrera
Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets. Int. J. Approx. Reason. 50 (3) (2009)
Alberto Fernández, María José del Jesus, Francisco Herrera
Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference System. IWANN (1) (2009)
Jesús Alcalá-Fdez, Salvador García, Francisco José Berlanga, Alberto Fernández, Luciano Sánchez, María José del Jesus, Francisco Herrera
KEEL: A data mining software tool integrating genetic fuzzy systems. GEFS (2008)
Alberto Fernández, Salvador García, María José del Jesus, Francisco Herrera
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets. Fuzzy Sets Syst. 159 (18) (2008)
Alberto Fernández, María José del Jesus, Francisco Herrera
A Short Study on the Use of Genetic 2-Tuples Tuning for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. HIS (2008)
Alberto Fernández, Salvador García, María José del Jesus, Francisco Herrera
A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets. IWANN (2007)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alberto Fernández