The effect of noise on the predictive limit of QSAR models
Abstract A key challenge in the field of Quantitative Structure Activity Relationships (QSAR) is how to effectively treat experimental error in the training and evaluation of computational models. It is often assumed in the field of QSAR that models cannot produce predictions which are more accurate...
Guardado en:
Autores principales: | Scott S. Kolmar, Christopher M. Grulke |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
BMC
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/78e54c4475464378b24bac9127e8e253 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Document similarity for error prediction
por: Péter Marjai, et al.
Publicado: (2021) -
Predictive Maintenance for Switch Machine Based on Digital Twins
por: Jia Yang, et al.
Publicado: (2021) -
THE EXPERT SYSTEM OF CONTROL AND KNOWLEDGE ASSESSMENT
por: V. Golovachyova, et al.
Publicado: (2020) -
Pattern Recognition of Human Face With Photos Using KNN Algorithm
por: Dedy Kurniadi, et al.
Publicado: (2021) -
Optimization and improvement of fake news detection using deep learning approaches for societal benefit
por: Tavishee Chauhan, M.E, et al.
Publicado: (2021)