Pedro J. García-Laencina

According to our database, Pedro J. García-Laencina authored at least 22 papers between 2005 and 2018.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2018

Improving the Classifier Performance in Motor Imagery Task Classification: What are the steps in the classification process that we should worry about?

Miriam Seoane Santos, Pedro H. Abreu, Germán Rodríguez-Bermúdez, Pedro J. García-Laencina

Int. J. Comput. Intell. Syst., 2018

2017

HCC Survival.

Miriam Seoane Santos, Pedro H. Abreu, Pedro J. García-Laencina, Adélia Simão, Armando Carvalho

Dataset, November, 2017

2015

A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients.

Miriam Seoane Santos, Pedro Henriques Abreu, Pedro J. García-Laencina, Adélia Simão, Armando Carvalho

J. Biomed. Informatics, 2015

Testing the Self-Similarity Exponent to Feature Extraction in Motor Imagery Based Brain Computer Interface Systems.

Germán Rodríguez-Bermúdez, Miguel Ángel Sánchez Granero, Pedro J. García-Laencina, Manuel Fernández-Martínez, José Serna, Joaquín Roca-Dorda

Int. J. Bifurc. Chaos, 2015

Missing data imputation on the 5-year survival prediction of breast cancer patients with unknown discrete values.

Pedro J. García-Laencina, Pedro Henriques Abreu, Miguel Henriques Abreu, Noémia Afonoso

Comput. Biol. Medicine, 2015

2014

Exploring dimensionality reduction of EEG features in motor imagery task classification.

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Joaquín Roca-Dorda

Expert Syst. Appl., 2014

2013

Neural architecture design based on extreme learning machine.

Andrés Bueno-Crespo, Pedro J. García-Laencina, José-Luis Sancho-Gómez

Neural Networks, 2013

Improving Predictions Using Linear Combination Of Multiple Extreme Learning Machines.

Pedro J. García-Laencina

Inf. Technol. Control., 2013

Efficient feature selection and linear discrimination of EEG signals.

Germán Rodríguez-Bermúdez, Pedro J. García-Laencina, Joaquín Roca-González, Joaquín Roca-Dorda

Neurocomputing, 2013

Efficient Automatic Selection and Combination of EEG Features in Least Squares Classifiers for Motor Imagery Brain-Computer Interfaces.

Germán Rodríguez-Bermúdez, Pedro J. García-Laencina, Joaquín Roca-Dorda

Int. J. Neural Syst., 2013

Classifying patterns with missing values using Multi-Task Learning perceptrons.

Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal

Expert Syst. Appl., 2013

2012

WIMP: Web server tool for missing data imputation.

Daniel Urda, José Luis Subirats, Pedro J. García-Laencina, Leonardo Franco, José-Luis Sancho-Gómez, José Manuel Jerez

Comput. Methods Programs Biomed., 2012

2010

Pattern classification with missing data: a review.

Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal

Neural Comput. Appl., 2010

Missing data imputation using statistical and machine learning methods in a real breast cancer problem.

José M. Jerez, Ignacio Molina, Pedro J. García-Laencina, Emilio Alba, Nuria Ribelles, Miguel Martín, Leonardo Franco

Artif. Intell. Medicine, 2010

2009

K nearest neighbours with mutual information for simultaneous classification and missing data imputation.

Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen

Neurocomputing, 2009

Combining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron.

José-Luis Sancho-Gómez, Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal

Intell. Autom. Soft Comput., 2009

2008

K-nearest neighbours based on mutual information for incomplete data classification.

Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

A Support Vector Method for Estimating Joint Density of Medical Images.

Jesús Serrano-García, Pedro J. García-Laencina, Jorge Larrey-Ruiz, José-Luis Sancho-Gómez

Proceedings of the Nature Inspired Problem-Solving Methods in Knowledge Engineering, 2007

Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles.

Santiago González-Benítez, Rafael Verdú, Rafael Berenguer, Pedro J. García-Laencina

Proceedings of the Nature Inspired Problem-Solving Methods in Knowledge Engineering, 2007

Multi-task Neural Networks for Dealing with Missing Inputs.

Pedro J. García-Laencina, Jesús Serrano-García, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez

Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

2006

Pattern Classification with Missing Values using Multitask Learning.

Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal

Proceedings of the International Joint Conference on Neural Networks, 2006

2005

Exploiting Multitask Learning Schemes Using Private Subnetworks.

Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal, Jesús Serrano-García, José-Luis Sancho-Gómez

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005