Nicolás García-Pedrajas
Orcid: 0000-0002-4488-6849Affiliations:
- University of Córdoba, Department of Computing, Córdoba, Spain
- University of Málaga, Málaga, Spain (PhD)
According to our database1,
Nicolás García-Pedrajas
authored at least 98 papers
between 1992 and 2024.
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Bibliography
2024
A thorough experimental comparison of multilabel methods for classification performance.
Pattern Recognit., 2024
Extensive experimental comparison among multilabel methods focused on ranking performance.
Inf. Sci., 2024
Evolutionary simultaneous under and oversampling of instances for dealing with class-imbalance datasets in multilabel problems.
Appl. Soft Comput., 2024
2023
PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification.
Inf. Fusion, July, 2023
2022
Nonlinear physics opens a new paradigm for accurate transcription start site prediction.
BMC Bioinform., December, 2022
IEEE Trans. Cybern., 2022
MABUSE: A margin optimization based feature subset selection algorithm using boosting principles.
Knowl. Based Syst., 2022
J. Chem. Inf. Model., 2022
Eng. Appl. Artif. Intell., 2022
2021
Floating Search Methodology for Combining Classification Models for Site Recognition in DNA Sequences.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features.
Pattern Recognit., 2021
Knowl. Based Syst., 2021
Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction.
J. Chem. Inf. Model., 2021
Instance selection for multi-label learning based on a scalable evolutionary algorithm.
Proceedings of the 2021 International Conference on Data Mining, 2021
2020
J. Cheminformatics, 2020
Influence of feature rankers in the construction of molecular activity prediction models.
J. Comput. Aided Mol. Des., 2020
Ensembles of feature selectors for dealing with class-imbalanced datasets: A proposal and comparative study.
Inf. Sci., 2020
2019
Pattern Recognit., 2019
Neural Networks, 2019
Multilabel and Missing Label Methods for Binary Quantitative Structure-Activity Relationship Models: An Application for the Prediction of Adverse Drug Reactions.
J. Chem. Inf. Model., 2019
2018
Combining three strategies for evolutionary instance selection for instance-based learning.
Swarm Evol. Comput., 2018
Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates.
J. Comput. Aided Mol. Des., 2018
Inf. Fusion, 2018
2017
IEEE Trans. Neural Networks Learn. Syst., 2017
A Study of SVM Kernel Functions for Sensitivity Classification Ensembles with POS Sequences.
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017
2016
Stepwise approach for combining many sources of evidence for site-recognition in genomic sequences.
BMC Bioinform., 2016
Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets.
Appl. Soft Comput., 2016
2015
Simultaneous instance and feature selection and weighting using evolutionary computation: Proposal and study.
Appl. Soft Comput., 2015
2014
Evol. Comput., 2014
Improving translation initiation site and stop codon recognition by using more than two classes.
Bioinform., 2014
Proceedings of the Ambient Intelligence - Software and Applications, 2014
Proceedings of the IEEE Fourth International Conference on Consumer Electronics Berlin, 2014
2013
IEEE Trans. Cybern., 2013
Boosting for class-imbalanced datasets using genetically evolved supervised non-linear projections.
Prog. Artif. Intell., 2013
Inf. Sci., 2013
2012
Proceedings of the Modern Advances in Intelligent Systems and Tools, 2012
Int. J. Knowl. Based Intell. Eng. Syst., 2012
Class imbalance methods for translation initiation site recognition in DNA sequences.
Knowl. Based Syst., 2012
Inf. Sci., 2012
Data Knowl. Eng., 2012
Multi-selection of instances: A straightforward way to improve evolutionary instance selection.
Appl. Soft Comput., 2012
Appl. Intell., 2012
A Comparative Study of Content Statistics of Coding Regions in an Evolutionary Computation Framework for Gene Prediction.
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012
Linear Projection Methods - An Experimental Study for Regression Problems.
Proceedings of the ICPRAM 2012, 2012
2011
WIREs Data Mining Knowl. Discov., 2011
An empirical study of binary classifier fusion methods for multiclass classification.
Inf. Fusion, 2011
Constructing ensembles of classifiers using supervised projection methods based on misclassified instances.
Expert Syst. Appl., 2011
Evolutionary computation, combined with support vector machines, for gene structure prediction.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
Proceedings of the Modern Approaches in Applied Intelligence, 2011
Proceedings of the Modern Approaches in Applied Intelligence, 2011
Proceedings of the Modern Approaches in Applied Intelligence, 2011
Instance Selection for Class Imbalanced Problems by Means of Selecting Instances More than Once.
Proceedings of the Advances in Artificial Intelligence, 2011
Proceedings of the Advances in Artificial Intelligence, 2011
2010
A cooperative coevolutionary algorithm for instance selection for instance-based learning.
Mach. Learn., 2010
Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts.
Artif. Intell., 2010
Proceedings of the Trends in Applied Intelligent Systems, 2010
Proceedings of the Trends in Applied Intelligent Systems, 2010
Proceedings of the Intelligent Data Engineering and Automated Learning, 2010
2009
IEEE Trans. Neural Networks, 2009
Expert Syst. Appl., 2009
A divide-and-conquer recursive approach for scaling up instance selection algorithms.
Data Min. Knowl. Discov., 2009
2008
Robust confidence intervals applied to crossover operator for real-coded genetic algorithms.
Soft Comput., 2008
J. Heuristics, 2008
Proceedings of the 13th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, 2008
Proceedings of the 13th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, 2008
Constructing ensembles of classifiers using linear projections based on misclassified instances.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008
2007
Pattern Recognit., 2007
Improving crossover operator for real-coded genetic algorithms using virtual parents.
J. Heuristics, 2007
2006
Proceedings of the Multi-Objective Machine Learning, 2006
Hybridization of evolutionary algorithms and local search by means of a clustering method.
IEEE Trans. Syst. Man Cybern. Part B, 2006
IEEE Trans. Pattern Anal. Mach. Intell., 2006
Neural Networks, 2006
An alternative approach for neural network evolution with a genetic algorithm: Crossover by combinatorial optimization.
Neural Networks, 2006
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
2005
Cooperative coevolution of artificial neural network ensembles for pattern classification.
IEEE Trans. Evol. Comput., 2005
CIXL2: A Crossover Operator for Evolutionary Algorithms Based on Population Features.
J. Artif. Intell. Res., 2005
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005
Proceedings of the IEEE Congress on Evolutionary Computation, 2005
2004
2003
IEEE Trans. Neural Networks, 2003
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003
2002
Multi-objective cooperative coevolution of artificial neural networks (multi-objective cooperative networks).
Neural Networks, 2002
Proceedings of the Parallel Problem Solving from Nature, 2002
Theoretical Analysis of the Confidence Interval Based Crossover for Real-Coded Genetic Algorithms.
Proceedings of the Parallel Problem Solving from Nature, 2002
2001
Introducing Multi-objective Optimization in Cooperative Coevolution of Neural Networks.
Proceedings of the Connectionist Models of Neurons, 2001
1992
Comparison Between Artificial Neural Networks and Classical Statsitical Methods in Pattern Recognition.
Proceedings of the IPMU '92, 1992