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ORCIDAlberto Fernández 0001
Person information
- affiliation: University of Granada, Department of Computer Science and Artificial Intelligence, Spain
- affiliation (former): University of Jaén, Department of Computer Science, Spain
Other persons with the same name
- Alberto Fernández (aka: Alberto Fernandez) — disambiguation page
- Alberto Fernández 0002
![[0000-0002-8962-6856]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-8962-6856")
(aka: Alberto Fernández Gil) — University Rey Juan Carlos, Mostoles, Spain - Alberto Fernández 0003 — Rovira i Virgili University, Tarragona, Spain
- Alberto Fernández 0004 — Complutense University of Madrid, Psychiatry Department, Spain
- Alberto Fernández 0005 (aka: Alberto Fernández González) — University College London, Bartlett School of Architecture, London, UK
- Alberto Fernández Villán (aka: Alberto Fernández 0006) — Grupo TSK, Gijón, Asturias, Spain (and 1 more)
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2020 – today
- 2024
[c43]J. Lopez-Martinez, Purificación Checa, José Manuel Soto-Hidalgo, Isaac Triguero, Alberto Fernández:
A Wearable Eye-Tracking Approach for Early Autism Detection with Machine Learning: Unravelling Challenges and Opportunities. IJCNN 2024: 1-8- [i3]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 abs/2405.12326 (2024) - [i2]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 abs/2407.14210 (2024) - 2023
- [j62]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: 228-253 (2023) - [j61]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): 3069-3080 (2023) - 2022
- [j60]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): 6207-6275 (2022) - [j59]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: 104791 (2022) - [j58]Xiangrui Chao, Gang Kou, Yi Peng, Alberto Fernández:
An efficiency curve for evaluating imbalanced classifiers considering intrinsic data characteristics: Experimental analysis. Inf. Sci. 608: 1131-1156 (2022) - [j57]Sebastián Maldonado, Carla Vairetti, Alberto Fernández, Francisco Herrera:
FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification. Pattern Recognit. 124: 108511 (2022) - [j56]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): 830-840 (2022) - 2021
- [j55]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: 514-524 (2021) - [j54]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): 1961-1989 (2021) - [j53]Néstor Rodríguez, David López, Alberto Fernández, Salvador García, Francisco Herrera:
SOUL: Scala Oversampling and Undersampling Library for imbalance classification. SoftwareX 15: 100767 (2021) - [e1]Pedro Henriques Abreu, Pedro Pereira Rodrigues, Alberto Fernández, João Gama:
Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings. Lecture Notes in Computer Science 12695, Springer 2021, ISBN 978-3-030-74250-8 [contents] - 2020
- [j52]Alberto Fernández:
Discussion on Vuttipittayamongkol, P. and Elyan, E., Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson's Disease. Int. J. Neural Syst. 30(9): 2075001:1-2075001:3 (2020) - [c42]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: 1-7 - [c41]José Ramón Trillo, Alberto Fernández, Francisco Herrera:
HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules. FUZZ-IEEE 2020: 1-8 - [c40]Nicolas Potie, Stavros Giannoukakos, Michael Hackenberg, Alberto Fernández:
Applying Feature Selection to Improve Predictive Performance and Explainability in Lung Cancer Detection with Soft Computing. HICSS 2020: 1-10 - [i1]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 abs/2007.07935 (2020)
2010 – 2019
- 2019
- [j51]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): 69-81 (2019) - [j50]Alberto Fernández, Isaac Triguero, Mikel Galar, Francisco Herrera:
Guest Editorial: Computational Intelligence for Big Data Analytics. Cogn. Comput. 11(3): 329-330 (2019) - [j49]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): 1321-1336 (2019) - [j48]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): 701-715 (2019) - [c39]Nicolas Potie, Stavros Giannoukakos, Michael Hackenberg, Alberto Fernández:
On the Need of Interpretability for Biomedical Applications: Using Fuzzy Models for Lung Cancer Prediction with Liquid Biopsy. FUZZ-IEEE 2019: 1-6 - [c38]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: 75-85 - 2018
- [b1]Alberto Fernández, Salvador García, Mikel Galar, Ronaldo C. Prati, Bartosz Krawczyk, Francisco Herrera:
Learning from Imbalanced Data Sets. Springer 2018, ISBN 978-3-319-98073-7, pp. 1-377 - [j47]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): 166:1-166:17 (2018) - [j46]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: 51-61 (2018) - [j45]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: 863-905 (2018) - [j44]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): 23 (2018) - [j43]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): 55-84 (2018) - [j42]Ignacio Cordón, Salvador García, Alberto Fernández, Francisco Herrera:
Imbalance: Oversampling algorithms for imbalanced classification in R. Knowl. Based Syst. 161: 329-341 (2018) - [c37]Luis Íñiguez, Mikel Galar, Alberto Fernández:
Improving Fuzzy Rule Based Classification Systems in Big Data via Support-based Filtering. FUZZ-IEEE 2018: 1-8 - 2017
- [j41]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): 711-730 (2017) - [j40]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): 1211-1225 (2017) - [j39]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): 1238-1249 (2017) - [j38]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): 1750028:1-1750028:21 (2017) - [j37]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: 26-51 (2017) - [c36]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: 1-6 - [c35]Miguel Ángel Rodríguez, Alberto Fernández, Antonio Peregrín, Francisco Herrera:
A Review of Distributed Data Models for Learning. HAIS 2017: 88-97 - 2016
- [j36]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: 108-122 (2016) - [j35]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): 69-80 (2016) - [j34]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: 178-196 (2016) - [c34]Alberto Fernández, Francisco Herrera:
Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification. Fuzzy Logic and Information Fusion 2016: 169-200 - [c33]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: 1437-1444 - 2015
- [j33]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): 193-202 (2015) - [j32]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: 1-17 (2015) - [j31]Alberto Fernández, Victoria López, María José del Jesus, Francisco Herrera:
Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges. Knowl. Based Syst. 80: 109-121 (2015) - [j30]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): 28-42 (2015) - [j29]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): 1562-1580 (2015) - [c32]Mikel Galar, Alberto Fernández, Edurne Barrenechea, Humberto Bustince, Francisco Herrera:
New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets. CORES 2015: 3-15 - [c31]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: 135-146 - [c30]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 - [c29]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: 1-7 - [c28]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: 1-7 - [c27]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: 36-44 - 2014
- [j28]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): 25-52 (2014) - [j27]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: 1-13 (2014) - [j26]Mikel Galar, Alberto Fernández, Edurne Barrenechea, Francisco Herrera:
Empowering difficult classes with a similarity-based aggregation in multi-class classification problems. Inf. Sci. 264: 135-157 (2014) - [j25]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): 380-409 (2014) - [c26]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: 1-8 - 2013
- [j24]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: 113-141 (2013) - [j23]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: 85-104 (2013) - [j22]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: 97-110 (2013) - [j21]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): 3412-3424 (2013) - [j20]Mikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Francisco Herrera:
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling. Pattern Recognit. 46(12): 3460-3471 (2013) - [j19]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): 399-411 (2013) - [c25]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: 1-8 - 2012
- [j18]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): 6585-6608 (2012) - [j17]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): 369-397 (2012) - [j16]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): 463-484 (2012) - [c24]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: 98-107 - [c23]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: 559-570 - [p1]Alberto Fernández, Francisco Herrera:
Linguistic Fuzzy Rules in Data Mining: Follow-Up Mamdani Fuzzy Modeling Principle. Combining Experimentation and Theory 2012: 103-122 - 2011
- [j15]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): 751-766 (2011) - [j14]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): 255-287 (2011) - [j13]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): 1761-1776 (2011) - [j12]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): 1909-1936 (2011) - [c22]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: 243-255 - [c21]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: 1239-1246 - [c20]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: 1247-1254 - [c19]Alberto Fernández, Salvador García, Francisco Herrera:
Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution. HAIS (1) 2011: 1-10 - [c18]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: 9-15 - 2010
- [j11]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): 3064-3080 (2010) - [j10]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): 1268-1291 (2010) - [j9]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): 2044-2064 (2010) - [j8]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): 3674-3685 (2010) - [j7]M. Dolores Pérez-Godoy, Alberto Fernández, Antonio Jesús Rivera Rivas, María José del Jesus:
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets. Pattern Recognit. Lett. 31(15): 2375-2388 (2010) - [j6]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): 913-941 (2010) - [c17]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: 1-3 - [c16]Alberto Fernández, María José del Jesus, Francisco Herrera:
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection. GEFS 2010: 69-74 - [c15]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: 89-98 - [c14]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: 741-750 - [c13]Victoria López, Alberto Fernández, Francisco Herrera:
A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets. ISDA 2010: 676-681
2000 – 2009
- 2009
- [j5]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): 1304-1314 (2009) - [j4]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): 9805-9812 (2009) - [j3]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): 561-577 (2009) - [j2]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): 959-977 (2009) - [c12]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: 42-47 - [c11]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: 1689-1694 - [c10]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: 581-588 - [c9]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: 562-569 - [c8]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: 523-528 - [c7]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: 57-64 - [c6]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: 294-301 - 2008
- [j1]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): 2378-2398 (2008) - [c5]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: 83-88 - [c4]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: 483-488 - 2007
- [c3]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: 375-382 - [c2]Alberto Fernández, Salvador García, Francisco Herrera, María José del Jesus:
An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets. WILF 2007: 170-178 - 2006
- [c1]Salvador García, José Ramón Cano, Alberto Fernández, Francisco Herrera:
A Proposal of Evolutionary Prototype Selection for Class Imbalance Problems. IDEAL 2006: 1415-1423
Coauthor Index
Humberto Bustince
aka: Humberto Bustince Sola
aka: Humberto Bustince Sola
[i3] [i2] [j57] [j55] [j54] [j53] [c41] [i1] [j51] [j50] [j49] [j48] [c38] [b1] [j47] [j46] [j45] [j44] [j43] [j42] [j41] [j40] [j39] [j38] [j37] [c36] [c35] [j36] [j35] [j34] [c34] [c33] [j33] [j32] [j31] [j30] [j29] [c32] [c31] [c30] [c29] [c28] [c27] [j28] [j27] [j26] [j25] [c26] [j24] [j23] [j22] [j21] [j20] [j19] [c25] [j18] [j17] [j16] [c24] [c23] [p1] [j15] [j13] [j12] [c22] [c21] [c20] [c19] [c18] [j11] [j10] [j9] [j8] [j6] [c17] [c16] [c15] [c14] [c13] [j5] [j4] [j3] [j2] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [j1] [c5] [c4] [c3] [c2] [c1]
Edurne Barrenechea Tartas
aka: Edurne Barrenechea
aka: Edurne Barrenechea
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