Assessing the behavior of machine learning methods to predict the activity of antimicrobial peptides
This study demonstrates the importance of obtaining statistically stable results when using machine learning methods to predict the activity of antimicrobial peptides, due to the cost and complexity of the chemical processes involved in cases where datasets are particularly small (less than a few hu...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14173
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5834
https://repositorio.uptc.edu.co/handle/001/14173
- Palabra clave:
- antimicrobial peptides
learning curves
machine learning
statistical stability
support vector regression
- Rights
- License
- http://purl.org/coar/access_right/c_abf191