César García-Osorio
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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
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
Nonlinear boosting projections for ensemble construction
N García-Pedrajas, C García-Osorio, C Fyfe
Journal of Machine Learning Research 8 (Jan), 1-33, 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
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
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
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), 521-532, 2011
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
Visualization of high-dimensional data via orthogonal curves
C Garcıa-Osorio, C Fyfe
Journal of Universal Computer Science 11 (11), 1806-1819, 2005
Supervised subspace projections for constructing ensembles of classifiers
N García-Pedrajas, J Maudes-Raedo, C García-Osorio, ...
Information Sciences 193, 1-21, 2012
Forests of nested dichotomies
JJ Rodríguez, C García-Osorio, J Maudes
Pattern Recognition Letters 31 (2), 125-132, 2010
Disturbing neighbors diversity for decision forests
J Maudes, JJ Rodríguez, C García-Osorio
Applications of supervised and unsupervised ensemble methods, 113-133, 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
Rotation Forests for regression
C Pardo, JF Diez-Pastor, C García-Osorio, JJ Rodríguez
Applied Mathematics and Computation 219 (19), 9914-9924, 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
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
Does the use of learning management systems with hypermedia mean improved student learning outcomes?
MC Sáiz-Manzanares, R Marticorena-Sánchez, JF Díez-Pastor, ...
Frontiers in psychology 10, 88, 2019
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
Instance selection for regression: Adapting DROP
Á Arnaiz-González, JF Díez-Pastor, JJ Rodríguez, C García-Osorio
Neurocomputing 201, 66-81, 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
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