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ORCIDÁlvar Arnaiz-González
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2020 – today
- 2024
[j21]Ismael Ramos-Pérez
, José Antonio Barbero-Aparicio, Antonio Canepa-Oneto, Álvar Arnaiz-González, Jesús Manuel Maudes Raedo:
An Extensive Performance Comparison between Feature Reduction and Feature Selection Preprocessing Algorithms on Imbalanced Wide Data. Inf. 15(4): 223 (2024)- 2023
- [c2]José Miguel Ramírez-Sanz, Helia Marina Peña-Alonso, Ana Serrano Mamolar, Álvar Arnaiz-González, Andrés Bustillo:
Detection of Stress Stimuli in Learning Contexts of iVR Environments. XR (2) 2023: 427-440 - 2022
- [j20]Ismael Ramos-Pérez, Álvar Arnaiz-González, Juan José Rodríguez, César García-Osorio:
When is resampling beneficial for feature selection with imbalanced wide data? Expert Syst. Appl. 188: 116015 (2022) - [j19]Juan José Rodríguez, Mario Juez-Gil, Carlos López Nozal, Álvar Arnaiz-González:
Rotation Forest for multi-target regression. Int. J. Mach. Learn. Cybern. 13(2): 523-548 (2022) - [j18]Juan José Rodríguez, Mario Juez-Gil, Carlos López Nozal, Álvar Arnaiz-González:
Correction to: Rotation Forest for multi-target regression. Int. J. Mach. Learn. Cybern. 13(2): 549-550 (2022) - 2021
- [j17]Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez, César García-Osorio:
Experimental evaluation of ensemble classifiers for imbalance in Big Data. Appl. Soft Comput. 108: 107447 (2021) - [j16]Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez, Carlos López Nozal, César García-Osorio:
Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark. Neurocomputing 464: 432-437 (2021) - [j15]Mario Juez-Gil, Álvar Arnaiz-González, Juan José Rodríguez Diez, Carlos López Nozal, César García-Osorio:
Rotation Forest for Big Data. Inf. Fusion 74: 39-49 (2021) - 2020
- [j14]Juan José Rodríguez, Mario Juez-Gil, Álvar Arnaiz-González, Ludmila I. Kuncheva:
An experimental evaluation of mixup regression forests. Expert Syst. Appl. 151: 113376 (2020) - [j13]Juan José Rodríguez, José-Francisco Díez-Pastor, Álvar Arnaiz-González, Ludmila I. Kuncheva:
Random Balance ensembles for multiclass imbalance learning. Knowl. Based Syst. 193: 105434 (2020) - [i3]Ludmila I. Kuncheva, Clare E. Matthews, Álvar Arnaiz-González, Juan José Rodríguez:
Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale. CoRR abs/2008.12025 (2020)
2010 – 2019
- 2019
- [j12]Miroslaw Kordos, Álvar Arnaiz-González, César García-Osorio:
Evolutionary prototype selection for multi-output regression. Neurocomputing 358: 309-320 (2019) - [j11]Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor, Iain A. D. Gunn:
Instance selection improves geometric mean accuracy: a study on imbalanced data classification. Prog. Artif. Intell. 8(2): 215-228 (2019) - 2018
- [j10]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César García-Osorio:
Local sets for multi-label instance selection. Appl. Soft Comput. 68: 651-666 (2018) - [j9]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Ismael Ramos-Pérez, César García-Osorio:
Seshat - a web-based educational resource for teaching the most common algorithms of lexical analysis. Comput. Appl. Eng. Educ. 26(6): 2255-2265 (2018) - [j8]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César García-Osorio:
Study of data transformation techniques for adapting single-label prototype selection algorithms to multi-label learning. Expert Syst. Appl. 109: 114-130 (2018) - [j7]Iain A. D. Gunn, Álvar Arnaiz-González, Ludmila I. Kuncheva:
A taxonomic look at instance-based stream classifiers. Neurocomputing 286: 167-178 (2018) - [i2]Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor, Iain A. D. Gunn:
Instance Selection Improves Geometric Mean Accuracy: A Study on Imbalanced Data Classification. CoRR abs/1804.07155 (2018) - 2017
- [j6]Álvar Arnaiz-González, Alejandro González-Rogel, José-Francisco Díez-Pastor, Carlos López Nozal:
MR-DIS: democratic instance selection for big data by MapReduce. Prog. Artif. Intell. 6(3): 211-219 (2017) - [i1]Álvar Arnaiz-González, Alejandro González-Rogel, Carlos López Nozal:
MR-DIS - A Scalable Instance Selection Algorithm using MapReduce on Spark. ERCIM News 2017(108) (2017) - 2016
- [j5]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César Ignacio García-Osorio:
Instance selection for regression by discretization. Expert Syst. Appl. 54: 340-350 (2016) - [j4]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César Ignacio García-Osorio:
Instance selection for regression: Adapting DROP. Neurocomputing 201: 66-81 (2016) - [j3]Álvar Arnaiz-González, Marcin Blachnik, Miroslaw Kordos, César Ignacio García-Osorio:
Fusion of instance selection methods in regression tasks. Inf. Fusion 30: 69-79 (2016) - [j2]Álvar Arnaiz-González, José-Francisco Díez-Pastor, Juan José Rodríguez, César Ignacio García-Osorio:
Instance selection of linear complexity for big data. Knowl. Based Syst. 107: 83-95 (2016) - [j1]Álvar Arnaiz-González, José-Francisco Díez-Pastor, César Ignacio García-Osorio, Juan José Rodríguez Diez:
Random feature weights for regression trees. Prog. Artif. Intell. 5(2): 91-103 (2016) - 2015
- [c1]Juan José Rodríguez Diez, José-Francisco Díez-Pastor, Álvar Arnaiz-González, César Ignacio García-Osorio:
An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees. MCS 2015: 181-193
Coauthor Index
aka: Juan José Rodríguez
aka: César García-Osorio
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last updated on 2024-08-05 20:22 CEST by the dblp team
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