Álvar Arnaiz-González

According to our database, Álvar Arnaiz-González authored at least 25 papers between 2015 and 2024.

Collaborative distances:

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

2024

An Extensive Performance Comparison between Feature Reduction and Feature Selection Preprocessing Algorithms on Imbalanced Wide Data.

Ismael Ramos-Pérez, José Antonio Barbero-Aparicio, Antonio Canepa-Oneto, Álvar Arnaiz-González, Jesús Manuel Maudes Raedo

Inf., April, 2024

2023

Detection of Stress Stimuli in Learning Contexts of iVR Environments.

José Miguel Ramírez-Sanz, Helia Marina Peña-Alonso, Ana Serrano Mamolar, Álvar Arnaiz-González, Andrés Bustillo

Proceedings of the Extended Reality - International Conference, 2023

2022

Correction to: Rotation Forest for multi-target regression.

Juan José Rodríguez, Mario Juez-Gil, Carlos López Nozal, Álvar Arnaiz-González

Int. J. Mach. Learn. Cybern., 2022

Rotation Forest for multi-target regression.

Juan José Rodríguez, Mario Juez-Gil, Carlos López Nozal, Álvar Arnaiz-González

Int. J. Mach. Learn. Cybern., 2022

When is resampling beneficial for feature selection with imbalanced wide data?

Ismael Ramos-Pérez, Álvar Arnaiz-González, Juan José Rodríguez, César García-Osorio

Expert Syst. Appl., 2022

2021

Rotation Forest for Big Data.

Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez Diez, Carlos López Nozal, César García-Osorio

Inf. Fusion, 2021

Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark.

Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez, Carlos López Nozal, César García-Osorio

Neurocomputing, 2021

Experimental evaluation of ensemble classifiers for imbalance in Big Data.

Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez, César García-Osorio

Appl. Soft Comput., 2021

2020

Random Balance ensembles for multiclass imbalance learning.

Juan José Rodríguez, José-Francisco Díez-Pastor, Álvar Arnaiz-González, Ludmila I. Kuncheva

Knowl. Based Syst., 2020

An experimental evaluation of mixup regression forests.

Juan José Rodríguez, Mario Juez-Gil, Álvar Arnaiz-González, Ludmila I. Kuncheva

Expert Syst. Appl., 2020

Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale.

Ludmila I. Kuncheva, Clare E. Matthews, Álvar Arnaiz-González, Juan José Rodríguez

CoRR, 2020

2019

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

Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor, Iain A. D. Gunn

Prog. Artif. Intell., 2019

Evolutionary prototype selection for multi-output regression.

Miroslaw Kordos, Álvar Arnaiz-González, César García-Osorio

Neurocomputing, 2019

2018

A taxonomic look at instance-based stream classifiers.

Iain A. D. Gunn, Álvar Arnaiz-González, Ludmila I. Kuncheva

Neurocomputing, 2018

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

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César García-Osorio

Expert Syst. Appl., 2018

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

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Ismael Ramos-Pérez, César García-Osorio

Comput. Appl. Eng. Educ., 2018

Local sets for multi-label instance selection.

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César García-Osorio

Appl. Soft Comput., 2018

2017

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

Álvar Arnaiz-González, Alejandro González-Rogel, José-Francisco Díez-Pastor, Carlos López Nozal

Prog. Artif. Intell., 2017

MR-DIS - A Scalable Instance Selection Algorithm using MapReduce on Spark.

Álvar Arnaiz-González, Alejandro González-Rogel, Carlos López Nozal

ERCIM News, 2017

2016

Random feature weights for regression trees.

Álvar Arnaiz-González, José-Francisco Díez-Pastor, César Ignacio García-Osorio, Juan José Rodríguez Diez

Prog. Artif. Intell., 2016

Instance selection of linear complexity for big data.

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez, César Ignacio García-Osorio

Knowl. Based Syst., 2016

Fusion of instance selection methods in regression tasks.

Álvar Arnaiz-González, Marcin Blachnik, Miroslaw Kordos, César Ignacio García-Osorio

Inf. Fusion, 2016

Instance selection for regression: Adapting DROP.

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César Ignacio García-Osorio

Neurocomputing, 2016

Instance selection for regression by discretization.

Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César Ignacio García-Osorio

Expert Syst. Appl., 2016

2015

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

Juan José Rodríguez Diez, José-Francisco Díez-Pastor, Álvar Arnaiz-González, César Ignacio García-Osorio

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