César García-Osorio

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Juan J. RodríguezUniversidad de BurgosVerified email at ubu.es
Álvar Arnaiz-GonzálezUniversidad de BurgosVerified email at ubu.es
Jesus MaudesProfesor de Informática (UBU)Verified email at ubu.es
Nicolas Garcia-PedrajasUniversity of CórdobaVerified email at uco.es
María Consuelo Sáiz ManzanaresProfesora de psicología evolutiva y de la educación en la Facultad de Ciencias de la Salud de laVerified email at ubu.es
Carlos Pardo AguilarUniversidad de BurgosVerified email at ubu.es
Ludmila KunchevaProfessor of Computer Science, Bangor University, UKVerified email at bangor.ac.uk
Raúl MarticorenaUniversidad de BurgosVerified email at ubu.es
Miguel Angel Queiruga DiosDepartamento de Didácticas Específicas. Universidad de BurgosVerified email at ubu.es
Andres BustilloUniversity of BurgosVerified email at ubu.es
Guillem QuintanaEurecat Technolgy Centre / Universitat de GironaVerified email at eurecat.org
Carlos López NozalProfesor Titular de Escuela UniversitariaVerified email at ubu.es
Miroslaw KordosUniversity of Bielsko-BialaVerified email at ath.bielsko.pl
Marcin BlachnikPolitechnika ŚląskaVerified email at polsl.pl
Joan Carles Melgarejo DraperDepartament de Mineralogia, Petrologia i Geologia AplicadaVerified email at ub.edu
Mario Juez-GilUniversidad de BurgosVerified email at ubu.es
Susana Jorge VillarUniversity of BurgosVerified email at ubu.es
Peter TinoProfessor of Complex and Adaptive Systems, University of Birmingham, UKVerified email at cs.bham.ac.uk
Ismael RamosUniversidad de BurgosVerified email at ubu.es
Juan Jose Saucedo-DorantesUniversidad Autonoma de QueretaroVerified email at hspdigital.org

César García-Osorio

Universidad de Burgos (Spain)

Verified email at ubu.es - Homepage

Data Mining Machine Learning Data Visualization Artificial Intelligence


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Random balance: ensembles of variable priors classifiers for imbalanced data JF Díez-Pastor, JJ Rodríguez, C Garcia-Osorio, LI Kuncheva Knowledge-Based Systems 85, 96-111, 2015	160	2015
Diversity techniques improve the performance of the best imbalance learning ensembles JF Díez-Pastor, JJ Rodríguez, CI García-Osorio, LI Kuncheva Information Sciences 325, 98-117, 2015	127	2015
Nonlinear boosting projections for ensemble construction N García-Pedrajas, C García-Osorio, C Fyfe Journal of Machine Learning Research 8 (Jan), 1-33, 2007	96	2007
Democratic instance selection: a linear complexity instance selection algorithm based on classifier ensemble concepts C García-Osorio, A de Haro-García, N García-Pedrajas Artificial Intelligence 174 (5-6), 410-441, 2010	89	2010
Random feature weights for decision tree ensemble construction J Maudes, JJ Rodríguez, C García-Osorio, N García-Pedrajas Information Fusion 13 (1), 20-30, 2012	54	2012
Instance selection of linear complexity for big data Á Arnaiz-González, JF Díez-Pastor, JJ Rodríguez, C García-Osorio Knowledge-Based Systems 107, 83-95, 2016	53	2016
Avoiding neural network fine tuning by using ensemble learning: application to ball-end milling operations A Bustillo, JF Díez-Pastor, G Quintana, C García-Osorio The International Journal of Advanced Manufacturing Technology 57 (5-8), 521, 2011	39	2011
Visualization of high-dimensional data via orthogonal curves C Garcıa-Osorio, C Fyfe Journal of Universal Computer Science 11 (11), 1806-1819, 2005	38	2005
How do B-Learning and learning patterns influence learning outcomes? MC Sáiz Manzanares, R Marticorena Sánchez, CI García Osorio, ... Frontiers in psychology 8, 745, 2017	34	2017
Supervised subspace projections for constructing ensembles of classifiers N García-Pedrajas, J Maudes-Raedo, C García-Osorio, ... Information Sciences 193, 1-21, 2012	34	2012
Forests of nested dichotomies JJ Rodríguez, C García-Osorio, J Maudes Pattern Recognition Letters 31 (2), 125-132, 2010	31	2010
Disturbing neighbors diversity for decision forests J Maudes, JJ Rodríguez, C García-Osorio Applications of supervised and unsupervised ensemble methods, 113-133, 2009	30	2009
Fusion of instance selection methods in regression tasks Á Arnaiz-González, M Blachnik, M Kordos, C García-Osorio Information Fusion 30, 69-79, 2016	26	2016
Rotation Forests for regression C Pardo, JF Diez-Pastor, C García-Osorio, JJ Rodríguez Applied Mathematics and Computation 219 (19), 9914-9924, 2013	24	2013
Constructing ensembles of classifiers using supervised projection methods based on misclassified instances N García-Pedrajas, C García-Osorio Expert Systems with Applications 38 (1), 343-359, 2011	24	2011
License plate number recognition-new heuristics and a comparative study of classifiers C Garcia-Osorio, JF Diez-Pastor, JJ Rodríguez, J Maudes Proceedings of the Fifth International Conference on Informatics in Control …, 2008	24	2008
A tool for teaching LL and LR parsing algorithms C García-Osorio, C Gómez-Palacios, N García-Pedrajas ACM SIGCSE Bulletin 40 (3), 317-317, 2008	21	2008
Random projections for linear SVM ensembles J Maudes, JJ Rodríguez, C García-Osorio, C Pardo Applied Intelligence 34 (3), 347-359, 2011	19	2011
Instance selection for regression: Adapting DROP Á Arnaiz-González, JF Díez-Pastor, JJ Rodríguez, C García-Osorio Neurocomputing 201, 66-81, 2016	18	2016
Instance selection for regression by discretization Á Arnaiz-González, JF Díez-Pastor, JJ Rodríguez, CI García-Osorio Expert Systems with Applications 54, 340-350, 2016	17	2016

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