TY  - JOUR 
AU  - Ramos Pérez, Ismael
AU  - Barbero Aparicio, José Antonio
AU  - Canepa Oneto, Antonio Jesús
AU  - Arnaiz González, Álvar
AU  - Maudes Raedo, Jesús M.
PY  - 2024
SN  - 2078-2489
UR  - https://hdl.handle.net/10259/11282
AB  - The most common preprocessing techniques used to deal with datasets having high dimensionality and a low number of instances—or wide data—are feature reduction (FR), feature selection (FS), and resampling. This study explores the use of FR and...
LA  - eng
PB  - MDPI
KW  - Feature selection
KW  - Feature reduction
KW  - Wide data
KW  - High dimensional data
KW  - Imbalanced data
KW  - Machine learning
KW  - Informática
KW  - Computer science
KW  - Inteligencia artificial
KW  - Artificial intelligence
TI  - An Extensive Performance Comparison between Feature Reduction and Feature Selection Preprocessing Algorithms on Imbalanced Wide Data
DO  - 10.3390/info15040223
T2  - Information
VL  - 15
M2  - 223
ER  -