Random forest algorithm-based classification model of pesticide aquatic toxicity to fishes

Author:

Yu XinliangORCID,Zeng Qun

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Aquatic Science

Reference25 articles.

1. Spatiotemporal land use random forest model for estimating metropolitan NO2 exposure in Japan;Araki;Sci. Total Environ.,2018

2. In silico prediction of the aniline derivatives toxicities to Tetrahymena pyriformis using chemometrics tools;Asadollahi-Baboli;Toxicol. Environ. Chem.,2012

3. Individual and combined toxicity of nitriles and aldehydes to Raphidocelis subcapitata;Chen;Environ. Toxicol. Chem.,2005

4. Application of chemometric methods and QSAR models to support pesticide risk assessment starting from ecotoxicological datasets;Galimberti;Water Res.,2020

5. EURL ECVAM Strategy to Replace, Reduce and Refine the Use of Fish in Aquatic Toxicity and Bioaccumulation Testing;Halder,2014

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