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ORCIDNicolás García-Pedrajas
Person information
- affiliation: University of Córdoba, Department of Computing, Córdoba, Spain
- affiliation (PhD): University of Málaga, Málaga, Spain
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2020 – today
- 2024
[j69]Nicolás García-Pedrajas
, José Manuel Cuevas-Muñoz, Aida de Haro-García:
Evolutionary simultaneous under and oversampling of instances for dealing with class-imbalance datasets in multilabel problems. Appl. Soft Comput. 159: 111618 (2024)- [j68]Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Gonzalo Cerruela García, Aida de Haro-García:
Extensive experimental comparison among multilabel methods focused on ranking performance. Inf. Sci. 679: 121074 (2024) - [j67]Nicolás García-Pedrajas:
Partial random under/oversampling for multilabel problems. Knowl. Based Syst. 302: 112355 (2024) - [j66]Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Gonzalo Cerruela García, Aida de Haro-García:
A thorough experimental comparison of multilabel methods for classification performance. Pattern Recognit. 151: 110342 (2024) - 2023
- [j65]Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Juan Antonio Romero del Castillo, Aida de Haro-García:
PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification. Inf. Fusion 95: 120-142 (2023) - 2022
- [j64]José Antonio Barbero-Aparicio, Santiago Cuesta-López, César Ignacio García-Osorio, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
Nonlinear physics opens a new paradigm for accurate transcription start site prediction. BMC Bioinform. 23(1): 565 (2022) - [j63]Juan Antonio Romero del Castillo, Manuel Mendoza-Hurtado, Domingo Ortiz-Boyer, Nicolás García-Pedrajas:
Local-based k values for multi-label k-nearest neighbors rule. Eng. Appl. Artif. Intell. 116: 105487 (2022) - [j62]Gonzalo Cerruela García, José Manuel Cuevas-Muñoz, Nicolás García-Pedrajas:
Graph-Based Feature Selection Approach for Molecular Activity Prediction. J. Chem. Inf. Model. 62(7): 1618-1632 (2022) - [j61]Nicolás García-Pedrajas, Gonzalo Cerruela García:
MABUSE: A margin optimization based feature subset selection algorithm using boosting principles. Knowl. Based Syst. 253: 109529 (2022) - [j60]Aida de Haro-García, José Pérez-Parras Toledano, Gonzalo Cerruela García, Nicolás García-Pedrajas:
Grab'Em: A Novel Graph-Based Method for Combining Feature Subset Selectors. IEEE Trans. Cybern. 52(5): 2942-2954 (2022) - 2021
- [j59]Aurelio Antelo-Collado, Ramón Carrasco-Velar, Nicolás García-Pedrajas, Gonzalo Cerruela García:
Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction. J. Chem. Inf. Model. 61(1): 76-94 (2021) - [j58]Nicolás García-Pedrajas, Gonzalo Cerruela García:
Cooperative coevolutionary instance selection for multilabel problems. Knowl. Based Syst. 234: 107569 (2021) - [j57]Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Gonzalo Cerruela García:
SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features. Pattern Recognit. 111: 107723 (2021) - [j56]Javier Pérez-Rodríguez, Aida de Haro-García, Nicolás García-Pedrajas:
Floating Search Methodology for Combining Classification Models for Site Recognition in DNA Sequences. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2471-2482 (2021) - [c28]Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer, Nicolás García-Pedrajas:
Instance selection for multi-label learning based on a scalable evolutionary algorithm. ICDM (Workshops) 2021: 843-851 - 2020
- [j55]Aida de Haro-García, Gonzalo Cerruela García, Nicolás García-Pedrajas:
Ensembles of feature selectors for dealing with class-imbalanced datasets: A proposal and comparative study. Inf. Sci. 540: 89-116 (2020) - [j54]Gonzalo Cerruela García, José Pérez-Parras Toledano, Aida de Haro-García, Nicolás García-Pedrajas:
Influence of feature rankers in the construction of molecular activity prediction models. J. Comput. Aided Mol. Des. 34(3): 305-325 (2020) - [j53]Aurelio Antelo-Collado, Ramón Carrasco-Velar, Nicolás García-Pedrajas, Gonzalo Cerruela García:
Maximum common property: a new approach for molecular similarity. J. Cheminformatics 12(1): 61 (2020)
2010 – 2019
- 2019
- [j52]José Pérez-Parras Toledano, Nicolás García-Pedrajas, Gonzalo Cerruela García:
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. 59(10): 4120-4130 (2019) - [j51]Gonzalo Cerruela García, Aida de Haro-García, José Pérez-Parras Toledano, Nicolás García-Pedrajas:
Improving the combination of results in the ensembles of prototype selectors. Neural Networks 118: 175-191 (2019) - [j50]Aida de Haro-García, Gonzalo Cerruela García, Nicolás García-Pedrajas:
Instance selection based on boosting for instance-based learners. Pattern Recognit. 96 (2019) - 2018
- [j49]Javier Pérez-Rodríguez, Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas:
A general framework for boosting feature subset selection algorithms. Inf. Fusion 44: 147-175 (2018) - [j48]Gonzalo Cerruela García, Nicolás García-Pedrajas:
Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates. J. Comput. Aided Mol. Des. 32(11): 1273-1294 (2018) - [j47]Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
Combining three strategies for evolutionary instance selection for instance-based learning. Swarm Evol. Comput. 42: 160-172 (2018) - 2017
- [j46]Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Gonzalo Cerruela García:
A Proposal for Local k Values for k-Nearest Neighbor Rule. IEEE Trans. Neural Networks Learn. Syst. 28(2): 470-475 (2017) - [c27]Graham McDonald, Nicolás García-Pedrajas, Craig Macdonald, Iadh Ounis:
A Study of SVM Kernel Functions for Sensitivity Classification Ensembles with POS Sequences. SIGIR 2017: 1097-1100 - 2016
- [j45]Nele Verbiest, Sarah Vluymans, Chris Cornelis, Nicolás García-Pedrajas, Yvan Saeys:
Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets. Appl. Soft Comput. 44: 75-88 (2016) - [j44]Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
Stepwise approach for combining many sources of evidence for site-recognition in genomic sequences. BMC Bioinform. 17: 117 (2016) - 2015
- [j43]Javier Pérez-Rodríguez, Alexis G. Arroyo-Peña, Nicolás García-Pedrajas:
Simultaneous instance and feature selection and weighting using evolutionary computation: Proposal and study. Appl. Soft Comput. 37: 416-443 (2015) - 2014
- [j42]Javier Pérez-Rodríguez, Alexis G. Arroyo-Peña, Nicolás García-Pedrajas:
Improving translation initiation site and stop codon recognition by using more than two classes. Bioinform. 30(19): 2702-2708 (2014) - [j41]Nicolás García-Pedrajas, Aida de Haro-García, Javier Pérez-Rodríguez:
A Scalable Memetic Algorithm for Simultaneous Instance and Feature Selection. Evol. Comput. 22(1): 1-45 (2014) - [j40]Nicolás García-Pedrajas, Aida de Haro-García:
Boosting instance selection algorithms. Knowl. Based Syst. 67: 342-360 (2014) - [c26]Gonzalo Cerruela García, Nicolás García-Pedrajas, Francisco José Bellido Outeiriño, Irene Luque Ruiz, Miguel Ángel Gómez-Nieto:
An ubiquitous system for advertising using mobile sensors and hand gestures. ICCE-Berlin 2014: 205-209 - [c25]Francisco Manuel Borrego-Jaraba, Gonzalo Cerruela García, Nicolás García-Pedrajas, Irene Luque Ruiz, Miguel Ángel Gómez-Nieto:
Mobile Solution Using NFC and In-Air Hand Gestures for Advertising Applications. ISAmI 2014: 135-142 - 2013
- [j39]Nicolás García-Pedrajas, Aida de Haro-García, Javier Pérez-Rodríguez:
A scalable approach to simultaneous evolutionary instance and feature selection. Inf. Sci. 228: 150-174 (2013) - [j38]Nicolás García-Pedrajas, César Ignacio García-Osorio:
Boosting for class-imbalanced datasets using genetically evolved supervised non-linear projections. Prog. Artif. Intell. 2(1): 29-44 (2013) - [j37]Nicolás García-Pedrajas, Javier Pérez-Rodríguez, Aida de Haro-García:
OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets. IEEE Trans. Cybern. 43(1): 332-346 (2013) - 2012
- [j36]Rafael del Castillo Gomariz, Nicolás García-Pedrajas:
Evolutionary response surfaces for classification: an interpretable model. Appl. Intell. 37(4): 463-474 (2012) - [j35]Nicolás García-Pedrajas, Javier Pérez-Rodríguez:
Multi-selection of instances: A straightforward way to improve evolutionary instance selection. Appl. Soft Comput. 12(11): 3590-3602 (2012) - [j34]Aida de Haro-García, Nicolás García-Pedrajas, Juan Antonio Romero del Castillo:
Large scale instance selection by means of federal instance selection. Data Knowl. Eng. 75: 58-77 (2012) - [j33]Jesús Maudes, Juan J. Rodríguez Diez, César Ignacio García-Osorio, Nicolás García-Pedrajas:
Random feature weights for decision tree ensemble construction. Inf. Fusion 13(1): 20-30 (2012) - [j32]Nicolás García-Pedrajas, Jesús Manuel Maudes Raedo, César Ignacio García-Osorio, Juan José Rodríguez Diez:
Supervised subspace projections for constructing ensembles of classifiers. Inf. Sci. 193: 1-21 (2012) - [j31]José Manuel Benítez, Nicolás García-Pedrajas, Francisco Herrera:
Special issue on "New Trends in Data Mining" NTDM. Knowl. Based Syst. 25(1): 1-2 (2012) - [j30]Nicolás García-Pedrajas, Javier Pérez-Rodríguez, María D. García-Pedrajas, Domingo Ortiz-Boyer, Colin Fyfe:
Class imbalance methods for translation initiation site recognition in DNA sequences. Knowl. Based Syst. 25(1): 22-34 (2012) - [j29]Colin Fyfe, Domingo Ortiz-Boyer, Nicolás García-Pedrajas:
Evolutionary algorithms and cross entropy. Int. J. Knowl. Based Intell. Eng. Syst. 16(4): 215-221 (2012) - [j28]Nicolás García-Pedrajas, Aida de Haro-García:
Scaling up data mining algorithms: review and taxonomy. Prog. Artif. Intell. 1(1): 71-87 (2012) - [c24]Carlos Pardo-Aguilar, José-Francisco Díez-Pastor, Nicolás García-Pedrajas, Juan José Rodríguez Diez, César Ignacio García-Osorio:
Linear Projection Methods - An Experimental Study for Regression Problems. ICPRAM (1) 2012: 198-204 - [c23]Javier Pérez-Rodríguez, Alexis G. Arroyo-Peña, Nicolás García-Pedrajas:
A Comparative Study of Content Statistics of Coding Regions in an Evolutionary Computation Framework for Gene Prediction. IEA/AIE 2012: 206-215 - [p2]Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
A Scalable Feature Selection Method to Improve the Analysis of Microarrays. Modern Advances in Intelligent Systems and Tools 2012: 87-92 - 2011
- [j27]Nicolás García-Pedrajas, Francisco Herrera, Colin Fyfe:
Special issue on the trends in applied intelligence systems. Appl. Intell. 34(3): 329-330 (2011) - [j26]Nicolás García-Pedrajas, César Ignacio García-Osorio:
Constructing ensembles of classifiers using supervised projection methods based on misclassified instances. Expert Syst. Appl. 38(1): 343-359 (2011) - [j25]Nicolás García-Pedrajas, Domingo Ortiz-Boyer:
An empirical study of binary classifier fusion methods for multiclass classification. Inf. Fusion 12(2): 111-130 (2011) - [j24]Nicolás García-Pedrajas:
Evolutionary computation for training set selection. WIREs Data Mining Knowl. Discov. 1(6): 512-523 (2011) - [c22]Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
A Comparison of Two Strategies for Scaling Up Instance Selection in Huge Datasets. CAEPIA 2011: 64-73 - [c21]Javier Pérez-Rodríguez, Aida de Haro-García, Nicolás García-Pedrajas:
Instance Selection for Class Imbalanced Problems by Means of Selecting Instances More than Once. CAEPIA 2011: 104-113 - [c20]Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
Feature Selection for Translation Initiation Site Recognition. IEA/AIE (2) 2011: 357-366 - [c19]Rafael del Castillo Gomariz, Nicolás García-Pedrajas:
Translation Initiation Site Recognition by Means of Evolutionary Response Surfaces. IEA/AIE (2) 2011: 376-385 - [c18]Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
An Evolutionary Algorithm for Gene Structure Prediction. IEA/AIE (2) 2011: 386-395 - [c17]Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
Evolutionary computation, combined with support vector machines, for gene structure prediction. ISDA 2011: 1359-1364 - [c16]Aida de Haro-García, Nicolás García-Pedrajas:
A scalable method for instance selection for class-imbalance datasets. ISDA 2011: 1383-1390 - [i1]Nicolás García-Pedrajas, César Hervás-Martínez, Domingo Ortiz-Boyer:
CIXL2: A Crossover Operator for Evolutionary Algorithms Based on Population Features. CoRR abs/1109.2146 (2011) - 2010
- [j23]César Ignacio García-Osorio, Aida de Haro-García, Nicolás García-Pedrajas:
Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts. Artif. Intell. 174(5-6): 410-441 (2010) - [j22]Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer:
A cooperative coevolutionary algorithm for instance selection for instance-based learning. Mach. Learn. 78(3): 381-420 (2010) - [c15]Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas:
Large Scale Instance Selection by Means of a Parallel Algorithm. IDEAL 2010: 1-12 - [c14]Nicolás García-Pedrajas, Domingo Ortiz-Boyer, María D. García-Pedrajas, Colin Fyfe:
Class Imbalance Methods for Translation Initiation Site Recognition. IEA/AIE (1) 2010: 327-336 - [c13]Aida de Haro-García, Nicolás García-Pedrajas:
Scaling Up Feature Selection by Means of Democratization. IEA/AIE (2) 2010: 662-672 - [e3]Nicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali:
Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part I. Lecture Notes in Computer Science 6096, Springer 2010, ISBN 978-3-642-13021-2 [contents] - [e2]Nicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali:
Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part II. Lecture Notes in Computer Science 6097, Springer 2010, ISBN 978-3-642-13024-3 [contents] - [e1]Nicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali:
Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part III. Lecture Notes in Computer Science 6098, Springer 2010, ISBN 978-3-642-13032-8 [contents]
2000 – 2009
- 2009
- [j21]Aida de Haro-García, Nicolás García-Pedrajas:
A divide-and-conquer recursive approach for scaling up instance selection algorithms. Data Min. Knowl. Discov. 18(3): 392-418 (2009) - [j20]Nicolás García-Pedrajas, Domingo Ortiz-Boyer:
Boosting k-nearest neighbor classifier by means of input space projection. Expert Syst. Appl. 36(7): 10570-10582 (2009) - [j19]Nicolás García-Pedrajas:
Supervised projection approach for boosting classifiers. Pattern Recognit. 42(9): 1742-1760 (2009) - [j18]Nicolás García-Pedrajas:
Constructing Ensembles of Classifiers by Means of Weighted Instance Selection. IEEE Trans. Neural Networks 20(2): 258-277 (2009) - 2008
- [j17]Nicolás García-Pedrajas, Colin Fyfe:
Construction of classifier ensembles by means of artificial immune systems. J. Heuristics 14(3): 285-310 (2008) - [j16]Nicolás García-Pedrajas, Domingo Ortiz-Boyer:
Boosting random subspace method. Neural Networks 21(9): 1344-1362 (2008) - [j15]Domingo Ortiz-Boyer, César Hervás-Martínez, Nicolás García-Pedrajas:
Robust confidence intervals applied to crossover operator for real-coded genetic algorithms. Soft Comput. 12(8): 809-833 (2008) - [j14]Nicolás García-Pedrajas, Colin Fyfe:
Evolving Output Codes for Multiclass Problems. IEEE Trans. Evol. Comput. 12(1): 93-106 (2008) - [c12]César Ignacio García-Osorio, Nicolás García-Pedrajas:
Constructing ensembles of classifiers using linear projections based on misclassified instances. ESANN 2008: 283-288 - [c11]César Ignacio García-Osorio, Iñigo Mediavilla-Sáiz, Javier Jimeno-Visitación, Nicolás García-Pedrajas:
Teaching push-down automata and turing machines. ITiCSE 2008: 316 - [c10]César Ignacio García-Osorio, Carlos Gómez-Palacios, Nicolás García-Pedrajas:
A tool for teaching LL and LR parsing algorithms. ITiCSE 2008: 317 - 2007
- [j13]Domingo Ortiz-Boyer, César Hervás-Martínez, Nicolás García-Pedrajas:
Improving crossover operator for real-coded genetic algorithms using virtual parents. J. Heuristics 13(3): 265-314 (2007) - [j12]Nicolás García-Pedrajas, Colin Fyfe:
Immune network based ensembles. Neurocomputing 70(7-9): 1155-1166 (2007) - [j11]Nicolás García-Pedrajas, César Ignacio García-Osorio, Colin Fyfe:
Nonlinear Boosting Projections for Ensemble Construction. J. Mach. Learn. Res. 8: 1-33 (2007) - [j10]Nicolás García-Pedrajas, Domingo Ortiz-Boyer:
A cooperative constructive method for neural networks for pattern recognition. Pattern Recognit. 40(1): 80-98 (2007) - 2006
- [j9]Alfonso C. Martínez-Estudillo, Francisco J. Martínez-Estudillo, César Hervás-Martínez, Nicolás García-Pedrajas:
Evolutionary product unit based neural networks for regression. Neural Networks 19(4): 477-486 (2006) - [j8]Nicolás García-Pedrajas, Domingo Ortiz-Boyer, César Hervás-Martínez:
An alternative approach for neural network evolution with a genetic algorithm: Crossover by combinatorial optimization. Neural Networks 19(4): 514-528 (2006) - [j7]Nicolás García-Pedrajas, Domingo Ortiz-Boyer:
Improving Multiclass Pattern Recognition by the Combination of Two Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 28(6): 1001-1006 (2006) - [j6]Alfonso C. Martínez-Estudillo, César Hervás-Martínez, Francisco J. Martínez-Estudillo, Nicolás García-Pedrajas:
Hybridization of evolutionary algorithms and local search by means of a clustering method. IEEE Trans. Syst. Man Cybern. Part B 36(3): 534-545 (2006) - [c9]Nicolás García-Pedrajas, Colin Fyfe:
Immune Network based Ensembles. ESANN 2006: 437-442 - [c8]Rafael del Castillo Gomariz, Nicolás García-Pedrajas:
Classification by means of Evolutionary Response Surfaces. ESANN 2006: 443-448 - [p1]Nicolás García-Pedrajas:
Cooperative Coevolution of Neural Networks and Ensembles of Neural Networks. Multi-Objective Machine Learning 2006: 465-490 - 2005
- [j5]Domingo Ortiz-Boyer, César Hervás-Martínez, Nicolás García-Pedrajas:
CIXL2: A Crossover Operator for Evolutionary Algorithms Based on Population Features. J. Artif. Intell. Res. 24: 1-48 (2005) - [j4]Nicolás García-Pedrajas, César Hervás-Martínez, Domingo Ortiz-Boyer:
Cooperative coevolution of artificial neural network ensembles for pattern classification. IEEE Trans. Evol. Comput. 9(3): 271-302 (2005) - [c7]Domingo Ortiz-Boyer, Rafael del Castillo Gomariz, Nicolás García-Pedrajas, César Hervás-Martínez:
Crossover effect over penalty methods in function optimization with constraints. Congress on Evolutionary Computation 2005: 1127-1134 - [c6]Nicolás García-Pedrajas, Domingo Ortiz-Boyer, Rafael del Castillo Gomariz, César Hervás-Martínez:
Cascade Ensembles. IWANN 2005: 598-603 - 2004
- [j3]Nicolás García-Pedrajas, Domingo Ortiz-Boyer, César Hervás-Martínez:
Cooperative coevolution of generalized multi-layer perceptrons. Neurocomputing 56: 257-283 (2004) - 2003
- [j2]Nicolás García-Pedrajas, César Hervás-Martínez, José Muñoz-Pérez:
COVNET: a cooperative coevolutionary model for evolving artificial neural networks. IEEE Trans. Neural Networks 14(3): 575-596 (2003) - [c5]Eloy Sanz-Tapia, Nicolás García-Pedrajas, Domingo Ortiz-Boyer, César Hervás-Martínez:
Node Level Crossover Applied to Neural Network Evolution. IWANN (1) 2003: 518-525 - 2002
- [j1]Nicolás García-Pedrajas, César Hervás-Martínez, José Muñoz-Pérez:
Multi-objective cooperative coevolution of artificial neural networks (multi-objective cooperative networks). Neural Networks 15(10): 1259-1278 (2002) - [c4]César Hervás-Martínez, Domingo Ortiz-Boyer, Nicolás García-Pedrajas:
Theoretical Analysis of the Confidence Interval Based Crossover for Real-Coded Genetic Algorithms. PPSN 2002: 153-161 - [c3]Domingo Ortiz-Boyer, César Hervás-Martínez, Nicolás García-Pedrajas:
Crossover Operator Effect in Function Optimization with Constraints. PPSN 2002: 184-193 - 2001
- [c2]Nicolás García-Pedrajas, Eloy Sanz-Tapia, Domingo Ortiz-Boyer, César Hervás-Martínez:
Introducing Multi-objective Optimization in Cooperative Coevolution of Neural Networks. IWANN (1) 2001: 645-652
1990 – 1999
- 1992
- [c1]César Hervás-Martínez, E. J. Romero Soto, Nicolás García-Pedrajas, Rafael Medina Carnicer:
Comparison Between Artificial Neural Networks and Classical Statsitical Methods in Pattern Recognition. IPMU 1992: 351-360
Coauthor Index
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