Francisco Fernández-Navarro
Francisco Fernández-Navarro
Dirección de correo verificada de - Página principal
Citado por
Citado por
Ordinal regression methods: survey and experimental study
PA Gutiérrez, M Perez-Ortiz, J Sanchez-Monedero, F Fernandez-Navarro, ...
IEEE Transactions on Knowledge and Data Engineering 28 (1), 127-146, 2015
A dynamic over-sampling procedure based on sensitivity for multi-class problems
F Fernández-Navarro, C Hervás-Martínez, PA Gutiérrez
Pattern Recognition 44 (8), 1821–1833, 2011
MELM-GRBF: A modified version of the extreme learning machine for generalized radial basis function neural networks
F Fernández-Navarro, C Hervás-Martínez, J Sánchez-Monedero, ...
Neurocomputing 74 (16), 2502-2510, 2011
PCA-ELM: a robust and pruned extreme learning machine approach based on principal component analysis
A Castaño, F Fernández-Navarro, C Hervás-Martínez
Neural processing letters 37 (3), 377-392, 2013
Evolutionary generalized radial basis function neural networks for improving prediction accuracy in gene classification using feature selection
F Fernández-Navarro, C Hervás-Martínez, R Ruiz, JC Riquelme
Applied Soft Computing 12 (6), 1787-1800, 2012
Cost-Sensitive AdaBoost Algorithm for Ordinal Regression Based on Extreme Learning Machine
A Riccardi, F Fernández-Navarro, S Carloni
IEEE Transaction on Cybernetics 44 (10), 1898 - 1909, 2014
Learner support in MOOCs: Identifying variables linked to completion
EB Gregori, J Zhang, C Galván-Fernández, F de Asís Fernández-Navarro
Computers & Education 122, 153-168, 2018
The Impact of Cultural Dimensions on Online Learning
P Gómez-Rey, E Barbera, F Fernández-Navarro
Educational Technology & Society 19 (4), 225-238, 2016
Parameter estimation of q-Gaussian Radial Basis Functions Neural Networks with a Hybrid Algorithm for binary classification
F Fernández-Navarro, C Hervás-Martínez, PA Gutiérrez, ...
Neurocomputing 75 (1), 123-134, 2012
Evolutionary q-Gaussian radial basis functions neural networks for multi-classification
F Fernández-Navarro, C Hervás-Martínez, PA Gutierrez, M Carboreno
Neural Networks 24 (7), 779–784, 2011
Negative Correlation Ensemble Learning for Ordinal Regression
F Fernandez-Navarro, PA Gutiérrez, C Hervás-Martínez, X Yao
IEEE Transactions on Neural Networks and Learning Systems 24 (11), 1836 - 1849, 2013
An experimental study of different ordinal regression methods and measures
P Gutiérrez, M Pérez-Ortiz, F Fernández-Navarro, J Sánchez-Monedero, ...
Hybrid Artificial Intelligent Systems - Lecture Notes in Computer Science …, 2012
Hybridizing logistic regression with product unit and RBF networks for accurate detection and prediction of banking crises
PA Gutiérrez, MJ Segovia-Vargas, S Salcedo-Sanz, C Hervás-Martínez, ...
Omega 38 (5), 333-344, 2010
Measuring teachers and learners’ perceptions of the quality of their online learning experience
P Gómez-Rey, E Barbera, F Fernández-Navarro
Distance Education 37 (2), 146-163, 2016
Development of a multi-classification neural network model to determine the microbial growth/no growth interface
F Fernández-Navarro, A Valero, C Hervás-Martínez, PA Gutiérrez, ...
International journal of food microbiology 141 (3), 203-212, 2010
Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm
A Nikolaou, PA Gutiérrez, A Durán, I Dicaire, F Fernández-Navarro, ...
Climate Dynamics 44 (7-8), 1919-1933, 2015
Addressing the EU Sovereign Ratings Using an Ordinal Regression Approach
F Fernandez-Navarro, P Campoy-Munoz, M Paz-Marin, ...
IEEE Transaction on Cybernetics 43 (6), 2228-2240, 2013
Global Sensitivity Estimates for Neural Network Classifiers.
F Fernández-Navarro, M Carbonero-Ruz, AD Becerra, M Torres-Jiménez
IEEE Transactions on Neural Networks and Learning Systems 28 (11), 2592-2604, 2017
Memetic pareto differential evolutionary artificial neural networks to determine growth multi-classes in predictive microbiology
M Cruz-Ramírez, J Sánchez-Monedero, F Fernández-Navarro, ...
Evolutionary intelligence 3 (3-4), 187-199, 2010
Ordinal Neural Networks Without Iterative Tuning
F Fernández-Navarro, A Riccardi, S Carloni
IEEE Transaction in Neural Networks and Learning Systems 25 (11), 2075-2085, 2014
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20