Jose M. Benitez
Jose M. Benitez
Full Professor, Universidad de Granada
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Cited by
Cited by
On the use of cross-validation for time series predictor evaluation
C Bergmeir, JM Benítez
Information Sciences 191, 192-213, 2012
A review of microarray datasets and applied feature selection methods
V Bolón-Canedo, N Sánchez-Marono, A Alonso-Betanzos, JM Benítez, ...
Information sciences 282, 111-135, 2014
Are artificial neural networks black boxes?
JM Benítez, JL Castro, I Requena
IEEE Transactions on neural networks 8 (5), 1156-1164, 1997
Big data preprocessing: methods and prospects
S García, S Ramírez-Gallego, J Luengo, JM Benítez, F Herrera
Big data analytics 1, 1-22, 2016
On the use of mapreduce for imbalanced big data using random forest
S Del Río, V López, JM Benítez, F Herrera
Information Sciences 285, 112-137, 2014
Neural networks in R using the Stuttgart neural network simulator: RSNNS
CN Bergmeir, JM Benítez Sánchez
American Statistical Association, 2012
Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation
C Bergmeir, RJ Hyndman, JM Benítez
International journal of forecasting 32 (2), 303-312, 2016
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks
A Fernández, S del Río, V López, A Bawakid, MJ del Jesus, JM Benítez, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 (5 …, 2014
Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data
V López, S Del Río, JM Benítez, F Herrera
Fuzzy Sets and Systems 258, 5-38, 2015
frbs: Fuzzy rule-based systems for classification and regression in R
LS Riza, C Bergmeir, F Herrera, JM Benítez
Journal of statistical software 65, 1-30, 2015
Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets”
LS Riza, A Janusz, C Bergmeir, C Cornelis, F Herrera, D Śle, JM Benítez
Information sciences 287, 68-89, 2014
A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation
D Peralta, M Galar, I Triguero, D Paternain, S García, E Barrenechea, ...
Information Sciences 315, 67-87, 2015
Data discretization: taxonomy and big data challenge
S Ramírez‐Gallego, S García, H Mouriño‐Talín, D Martínez‐Rego, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 6 (1), 5-21, 2016
ROSEFW-RF: the winner algorithm for the ECBDL’14 big data competition: an extremely imbalanced big data bioinformatics problem
I Triguero, S Del Río, V López, J Bacardit, JM Benítez, F Herrera
Knowledge-Based Systems 87, 69-79, 2015
Fuzzy control of HVAC systems optimized by genetic algorithms
R Alcalá, JM Benítez, J Casillas, O Cordón, R Pérez
Applied Intelligence 18, 155-177, 2003
Evolutionary feature selection for big data classification: A mapreduce approach
D Peralta, S Del Río, S Ramírez-Gallego, I Triguero, JM Benitez, ...
Mathematical Problems in Engineering 2015 (1), 246139, 2015
Fast‐mRMR: Fast minimum redundancy maximum relevance algorithm for high‐dimensional big data
S Ramírez‐Gallego, I Lastra, D Martínez‐Rego, V Bolón‐Canedo, ...
International Journal of Intelligent Systems 32 (2), 134-152, 2017
Artificial neural network-based equation for estimating VO2max from the 20 m shuttle run test in adolescents
JR Ruiz, J Ramirez-Lechuga, FB Ortega, J Castro-Pinero, JM Benitez, ...
Artificial intelligence in medicine 44 (3), 233-245, 2008
An overview of e-learning in cloud computing
A Fernandez, D Peralta, F Herrera, JM Benítez
Workshop on Learning Technology for Education in Cloud (LTEC'12), 35-46, 2012
Interpretation of artificial neural networks by means of fuzzy rules
JL Castro, CJ Mantas, JM Benítez
IEEE Transactions on Neural Networks 13 (1), 101-116, 2002
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