José-Francisco Díez-Pastor

José Antonio Barbero-Aparicio

Inf. Fusion, February, 2024

2023

Deep learning and support vector machines for transcription start site identification.

[BibT_eX]

[DOI]

Alicia Olivares-Gil

PeerJ Comput. Sci., 2023

2022

Defect detection and segmentation in X-Ray images of magnesium alloy castings using the Detectron2 framework.

[BibT_eX]

[DOI]

Francisco Javier Yagüe

Pedro Latorre Carmona

María Consuelo Sáiz-Manzanares

CoRR, 2022

2021

Improve teaching with modalities and collaborative groups in an LMS: an analysis of monitoring using visualisation techniques.

[BibT_eX]

[DOI]

Raúl Marticorena Sánchez

Sandra Rodríguez-Arribas

Yi Peng Ji

J. Comput. High. Educ., 2021

2020

Random Balance ensembles for multiclass imbalance learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2020

2019

Instance selection improves geometric mean accuracy: a study on imbalanced data classification.

[BibT_eX]

[DOI]

Iain A. D. Gunn

Prog. Artif. Intell., 2019

2018

Study of data transformation techniques for adapting single-label prototype selection algorithms to multi-label learning.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2018

Seshat - a web-based educational resource for teaching the most common algorithms of lexical analysis.

[BibT_eX]

[DOI]

Ismael Ramos-Pérez

Comput. Appl. Eng. Educ., 2018

Local sets for multi-label instance selection.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2018

2017

MR-DIS: democratic instance selection for big data by MapReduce.

[BibT_eX]

[DOI]

Alejandro González-Rogel

Carlos López Nozal

Prog. Artif. Intell., 2017

2016

Random feature weights for regression trees.

[BibT_eX]

[DOI]

Prog. Artif. Intell., 2016

Instance selection of linear complexity for big data.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2016

Instance selection for regression: Adapting DROP.

[BibT_eX]

[DOI]

Neurocomputing, 2016

Instance selection for regression by discretization.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2016

2015

Random Balance: Ensembles of variable priors classifiers for imbalanced data.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2015

Diversity techniques improve the performance of the best imbalance learning ensembles.

[BibT_eX]

[DOI]

Inf. Sci., 2015

An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the Multiple Classifier Systems - 12th International Workshop, 2015

2014

Tree ensemble construction using a GRASP-based heuristic and annealed randomness.

[BibT_eX]

[DOI]

Inf. Fusion, 2014

2013

An Innovative Moodle Final Project Management Module for Bachelor and Master's Studies.

[BibT_eX]

[DOI]

Carlos López Nozal

Jesús Manuel Maudes Raedo

Raúl Marticorena Sánchez

Rev. Iberoam. de Tecnol. del Aprendiz., 2013

Rotation Forests for regression.

[BibT_eX]

[DOI]

Carlos Pardo

Appl. Math. Comput., 2013

Random Oracle Ensembles for Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Multiple Classifier Systems, 11th International Workshop, 2013

Imbalanced Learning Ensembles for Defect Detection in X-Ray Images.

[BibT_eX]

[DOI]

Víctor Barbero-García

Alan Blanco-Álamo

Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

2012

Boosting Projections to improve surface roughness prediction in high-torque milling operations.

[BibT_eX]

[DOI]

Andrés Bustillo

Guillem Quintana

Soft Comput., 2012

Módulo Moodle para Gestionar Trabajos Final de Grado o Máster.

[BibT_eX]

[DOI]

Carlos López Nozal

Jesús Manuel Maudes Raedo

Raúl Marticorena Sánchez

Rev. Iberoam. de Tecnol. del Aprendiz., 2012

Linear Projection Methods - An Experimental Study for Regression Problems.

[BibT_eX]

Carlos Pardo-Aguilar

Nicolás García-Pedrajas

Proceedings of the ICPRAM 2012, 2012

Disturbing Neighbors Ensembles of Trees for Imbalanced Data.

[BibT_eX]

[DOI]

Jesús Maudes

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2011

Random Oracles for Regression Ensembles.

[BibT_eX]

[DOI]

Carlos Pardo

Juan J. Rodríguez Diez

Proceedings of the Ensembles in Machine Learning Applications, 2011

Ensembles of Decision Trees for Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

GRASP Forest: A New Ensemble Method for Trees.

[BibT_eX]

[DOI]

Andrés Bustillo

Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

Using Model Trees and Their Ensembles for Imbalanced Data.

[BibT_eX]

[DOI]

Juan J. Rodríguez Diez

Pedro Santos

Proceedings of the Advances in Artificial Intelligence, 2011

2010

An Experimental Study on Ensembles of Functional Trees.

[BibT_eX]

[DOI]

Jesús Maudes

Proceedings of the Multiple Classifier Systems, 9th International Workshop, 2010

2008

License Plate Number Recognition - New Heuristics and a Comparative Study of Classifiers.

[BibT_eX]