Cargando…
Random forests for feature selection in QSPR Models - an application for predicting standard enthalpy of formation of hydrocarbons
BACKGROUND: One of the main topics in the development of quantitative structure-property relationship (QSPR) predictive models is the identification of the subset of variables that represent the structure of a molecule and which are predictors for a given property. There are several automated featur...
Autores principales: | Teixeira, Ana L, Leal, João P, Falcao, Andre O |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599435/ https://www.ncbi.nlm.nih.gov/pubmed/23399299 http://dx.doi.org/10.1186/1758-2946-5-9 |
Ejemplares similares
-
Prediction of Standard Enthalpy of Formation by a QSPR Model
por: Vatani, Ali, et al.
Publicado: (2007) -
Predicting the Enthalpy and Gibbs Energy of Sublimation by QSPR Modeling
por: Meftahi, Nastaran, et al.
Publicado: (2018) -
An Improved QSPR Modeling of Hydrocarbon Dipole Moments
por: Nesterov, Igor V., et al.
Publicado: (2004) -
Correction: Vatani, A., et al. Prediction of Standard Enthalpy of Formation by a QSPR Model. Int. J. Mol. Sci. 2007, 8, 407–432.
por: Vatani, Ali, et al.
Publicado: (2009) -
Data Science Approach to Estimate Enthalpy of Formation
of Cyclic Hydrocarbons
por: Yalamanchi, Kiran K., et al.
Publicado: (2020)