An Ar2p Deep Learning Architecture for the Discovery and the Selection of Features
In the context of pattern recognition processes with machine learning algorithms, either through supervised, semi-supervised or unsupervised methods, one of the most important elements to consider are the features that are used to represent the phenomenon to be studied. In this sense, this paper pro...
- Autores:
-
Aguilar, Jose
Puerto, E.
Vargas, R.
Reyes, J.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Universidad Francisco de Paula Santander
- Repositorio:
- Repositorio Digital UFPS
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.ufps.edu.co:ufps/1642
- Acceso en línea:
- http://repositorio.ufps.edu.co/handle/ufps/1642
https://doi.org/10.1007/s11063-019-10062-4
- Palabra clave:
- Deep learning
Pattern recognition processes
Feature engineering
Pattern Recognition Theory of Mind
- Rights
- openAccess
- License
- © 2021 Springer Nature Switzerland AG. Part of Springer Nature.