Nicolás García-Pedrajas

Orcid: 0000-0002-4488-6849

Affiliations:
  • 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.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A thorough experimental comparison of multilabel methods for classification performance.
Pattern Recognit., 2024

Partial random under/oversampling for multilabel problems.
Knowl. Based Syst., 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

Grab'Em: A Novel Graph-Based Method for Combining Feature Subset Selectors.
IEEE Trans. Cybern., 2022

MABUSE: A margin optimization based feature subset selection algorithm using boosting principles.
Knowl. Based Syst., 2022

Graph-Based Feature Selection Approach for Molecular Activity Prediction.
J. Chem. Inf. Model., 2022

Local-based k values for multi-label k-nearest neighbors rule.
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

Cooperative coevolutionary instance selection for multilabel problems.
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
Maximum common property: a new approach for molecular similarity.
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
Instance selection based on boosting for instance-based learners.
Pattern Recognit., 2019

Improving the combination of results in the ensembles of prototype selectors.
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

A general framework for boosting feature subset selection algorithms.
Inf. Fusion, 2018

2017
A Proposal for Local k Values for k-Nearest Neighbor Rule.
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
Boosting instance selection algorithms.
Knowl. Based Syst., 2014

A Scalable Memetic Algorithm for Simultaneous Instance and Feature Selection.
Evol. Comput., 2014

Improving translation initiation site and stop codon recognition by using more than two classes.
Bioinform., 2014

Mobile Solution Using NFC and In-Air Hand Gestures for Advertising Applications.
Proceedings of the Ambient Intelligence - Software and Applications, 2014

An ubiquitous system for advertising using mobile sensors and hand gestures.
Proceedings of the IEEE Fourth International Conference on Consumer Electronics Berlin, 2014

2013
OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.
IEEE Trans. Cybern., 2013

Boosting for class-imbalanced datasets using genetically evolved supervised non-linear projections.
Prog. Artif. Intell., 2013

A scalable approach to simultaneous evolutionary instance and feature selection.
Inf. Sci., 2013

2012
A Scalable Feature Selection Method to Improve the Analysis of Microarrays.
Proceedings of the Modern Advances in Intelligent Systems and Tools, 2012

Scaling up data mining algorithms: review and taxonomy.
Prog. Artif. Intell., 2012

Evolutionary algorithms and cross entropy.
Int. J. Knowl. Based Intell. Eng. Syst., 2012

Class imbalance methods for translation initiation site recognition in DNA sequences.
Knowl. Based Syst., 2012

Special issue on "New Trends in Data Mining" NTDM.
Knowl. Based Syst., 2012

Supervised subspace projections for constructing ensembles of classifiers.
Inf. Sci., 2012

Random feature weights for decision tree ensemble construction.
Inf. Fusion, 2012

Large scale instance selection by means of federal instance selection.
Data Knowl. Eng., 2012

Multi-selection of instances: A straightforward way to improve evolutionary instance selection.
Appl. Soft Comput., 2012

Evolutionary response surfaces for classification: an interpretable model.
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
Evolutionary computation for training set selection.
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

Special issue on the trends in applied intelligence systems.
Appl. Intell., 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

A scalable method for instance selection for class-imbalance datasets.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

An Evolutionary Algorithm for Gene Structure Prediction.
Proceedings of the Modern Approaches in Applied Intelligence, 2011

Feature Selection for Translation Initiation Site Recognition.
Proceedings of the Modern Approaches in Applied Intelligence, 2011

Translation Initiation Site Recognition by Means of Evolutionary Response Surfaces.
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

A Comparison of Two Strategies for Scaling Up Instance Selection in Huge Datasets.
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

Scaling Up Feature Selection by Means of Democratization.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Class Imbalance Methods for Translation Initiation Site Recognition.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Large Scale Instance Selection by Means of a Parallel Algorithm.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2010

2009
Constructing Ensembles of Classifiers by Means of Weighted Instance Selection.
IEEE Trans. Neural Networks, 2009

Supervised projection approach for boosting classifiers.
Pattern Recognit., 2009

Boosting k-nearest neighbor classifier by means of input space projection.
Expert Syst. Appl., 2009

A divide-and-conquer recursive approach for scaling up instance selection algorithms.
Data Min. Knowl. Discov., 2009

2008
Evolving Output Codes for Multiclass Problems.
IEEE Trans. Evol. Comput., 2008

Robust confidence intervals applied to crossover operator for real-coded genetic algorithms.
Soft Comput., 2008

Boosting random subspace method.
Neural Networks, 2008

Construction of classifier ensembles by means of artificial immune systems.
J. Heuristics, 2008

Teaching push-down automata and turing machines.
Proceedings of the 13th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, 2008

A tool for teaching LL and LR parsing algorithms.
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
A cooperative constructive method for neural networks for pattern recognition.
Pattern Recognit., 2007

Nonlinear Boosting Projections for Ensemble Construction.
J. Mach. Learn. Res., 2007

Immune network based ensembles.
Neurocomputing, 2007

Improving crossover operator for real-coded genetic algorithms using virtual parents.
J. Heuristics, 2007

2006
Cooperative Coevolution of Neural Networks and Ensembles of Neural Networks.
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

Improving Multiclass Pattern Recognition by the Combination of Two Strategies.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

Evolutionary product unit based neural networks for regression.
Neural Networks, 2006

An alternative approach for neural network evolution with a genetic algorithm: Crossover by combinatorial optimization.
Neural Networks, 2006

Classification by means of Evolutionary Response Surfaces.
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

Cascade Ensembles.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Crossover effect over penalty methods in function optimization with constraints.
Proceedings of the IEEE Congress on Evolutionary Computation, 2005

2004
Cooperative coevolution of generalized multi-layer perceptrons.
Neurocomputing, 2004

2003
COVNET: a cooperative coevolutionary model for evolving artificial neural networks.
IEEE Trans. Neural Networks, 2003

Node Level Crossover Applied to Neural Network Evolution.
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

Crossover Operator Effect in Function Optimization with Constraints.
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


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