Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum
Assessment of the risk of chemicals is an important task in the environmental protection. In
this paper, we developed quantitative structure–activity relationship (QSAR) methods to
evaluate the toxicity of phenol to Photobacterium phosphoreum, which is an important
indicator for water quality. We first built support vector regression (SVR) model using three
descriptors, and the SVR model (t= 2) had the highest external prediction ability (MSE ext=
0.068, Q ext 2= 0.682), about 40% higher than literature model's. Second, to identify more …
this paper, we developed quantitative structure–activity relationship (QSAR) methods to
evaluate the toxicity of phenol to Photobacterium phosphoreum, which is an important
indicator for water quality. We first built support vector regression (SVR) model using three
descriptors, and the SVR model (t= 2) had the highest external prediction ability (MSE ext=
0.068, Q ext 2= 0.682), about 40% higher than literature model's. Second, to identify more …
以上显示的是最相近的搜索结果。 查看全部搜索结果