Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/162975
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Using explanations for determining carcinogenecity in chemical compounds |
Autor: | Armengol, Eva CSIC ORCID | Palabras clave: | Predictive toxicology Partial domain models Lazy learning Lazy induction of descriptions Explanations Feature terms |
Fecha de publicación: | 2009 | Editor: | Elsevier | Citación: | Engineering Applications of Artificial Intelligence 22: 10- 17 (2009) | Resumen: | The goal of predictive toxicology is the automatic construction of carcinogenecity models. Most common artificial intelligence techniques used to construct these models are inductive learning methods. In a previous work we presented an approach that uses lazy learning methods for solving the problem of predicting carcinogenecity. Lazy learning methods solve new problems based on their similarity to already solved problems. Nevertheless, a weakness of these kind of methods is that sometimes the result is not completely understandable by the user. In this paper we propose an explanation scheme for a concrete lazy learning method. This scheme is particularly interesting to justify the predictions about the carcinogenesis of chemical compounds. In addition we propose that these explanations could be used to build a partial domain knowledge. In our particular case, we use the explanations for building general knowledge about carcinogenesis. © 2008 Elsevier Ltd. All rights reserved. | URI: | http://hdl.handle.net/10261/162975 | DOI: | 10.1016/j.engappai.2008.04.004 | Identificadores: | doi: 10.1016/j.engappai.2008.04.004 issn: 0952-1976 |
Aparece en las colecciones: | (IIIA) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
accesoRestringido.pdf | 15,38 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
1
checked on 11-abr-2024
WEB OF SCIENCETM
Citations
1
checked on 23-feb-2024
Page view(s)
224
checked on 18-abr-2024
Download(s)
76
checked on 18-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.