Interpretation of QSAR Models Based on Random Forest Methods

By V. Kuz'min, Pavel G. Polishchuk, Anatoly G. Artemenko, S. Andronati. 2011

77 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Spectroscopy

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1. Soeren H. Welling

Citations in the corpus

• Forest Floor Visualizations of Random Forests (2016, methodology): “Properties of the RF algorithm by Breimann [3] and the feature contributions method by Kuz’min et al [9] and Palczewska et al [16] are highlighted and illustrated in section 2.2.”
• QSAR Modeling: Where have you been? Where are you going to? (2014, unknown): “and the ecological structure−activity relationships (ECOSAR) software for predicting aquatic toxicity of compounds.(282) The latter tool has also been demonstrated to have some useful applicability to pharmaceuticals.(283) Worldwide, QSAR methods have been used for identification of potential health”