Pedro J. García-Laencina

发表

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

Leonardo Franco, José M. Jerez, Ignacio Molina, 2010, Artif. Intell. Medicine.

Multi-task Neural Networks for Dealing with Missing Inputs

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2007, IWINAC.

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

Michel Verleysen, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, 2008, ESANN.

Exploring dimensionality reduction of EEG features in motor imagery task classification

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Joaquín Roca-Dorda, 2014, Expert Syst. Appl..

Classification with Incomplete Data

Aníbal R. Figueiras-Vidal, Juan Morales-Sánchez, Jorge Larrey-Ruiz, 2010 .

Efficient feature selection and linear discrimination of EEG signals

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Joaquín Roca-Dorda, 2013, Neurocomputing.

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

Pedro Abreu, Pedro J. García-Laencina, Miguel Henriques Abreu, 2015, Comput. Biol. Medicine.

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

Michel Verleysen, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, 2009, Neurocomputing.

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

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Joaquín Roca-Dorda, 2013, Int. J. Neural Syst..

Exploiting Multitask Learning Schemes Using Private Subnetworks

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2005, IWANN.

Pattern classification with missing data: a review

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2010, Neural Computing and Applications.

Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles

Rafael Verdú, Rafael Berenguer-Vidal, Pedro J. García-Laencina, 2007, IWINAC.

Improving Predictions Using Linear Combination Of Multiple Extreme Learning Machines

Pedro J. García-Laencina, 2013, Inf. Technol. Control..

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

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2009, Intell. Autom. Soft Comput..

Technological Immersion in Industrial Engineering for a Project Management Course to Develop Dual Use Technology

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Antonio Juan Briones-Peñalver, 2017 .

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

Miriam Seoane Santos, Pedro Abreu, Pedro J. García-Laencina, 2015, J. Biomed. Informatics.

A Support Vector Method for Estimating Joint Density of Medical Images

Jorge Larrey-Ruiz, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2007, IWINAC.

Pattern Classification with Missing Values using Multitask Learning

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Classifying patterns with missing values using Multi-Task Learning perceptrons

Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2013, Expert Syst. Appl..

Statistical Data Mining and Artificial Neural Networks: A Case of Study in Financial Modeling

Pedro J. García-Laencina, Joaquín Roca-Dorda, Carmen de Nieves-Nieto, 2012 .

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

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, Joaquín Roca-Dorda, 2015, Int. J. Bifurc. Chaos.

Automatic and Adaptive Classification of Electroencephalographic Signals for Brain Computer Interfaces

Pedro J. García-Laencina, Germán Rodríguez-Bermúdez, P. J. García-Laencina, 2012, Journal of Medical Systems.

Neural architecture design based on extreme learning machine

Andrés Bueno-Crespo, José-Luis Sancho-Gómez, Pedro J. García-Laencina, 2013, Neural Networks.

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, Pedro J. García-Laencina, 2018, Int. J. Comput. Intell. Syst..