Application of random forests method to predict the retention indices of some polycyclic aromatic hydrocarbons was written by Goudarzi, N.;Shahsavani, D.;Emadi-Gandaghi, F.;Chamjangali, M. Arab. And the article was included in Journal of Chromatography A in 2014.Electric Literature of C16H10O This article mentions the following:
A quant. structure-retention relation (QSRR) study was carried out based on the new method of random forests (RF) for prediction of the retention indexes (RIs) of some polycyclic aromatic hydrocarbon (PAH) compounds The RIs of these compounds were calculated using the theor. descriptors generated from their mol. structures. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were studied. Optimization of these parameters showed that in the point m = 70, nt = 460, the RF method can give the best results. Also, performance of the RF model was compared with that of the artificial neural network (ANN) and multiple linear regression (MLR) techniques. The results obtained show the relative superiority of the RF method over the MLR and ANN ones. In the experiment, the researchers used many compounds, for example, Naphtho[2,1-b]benzofuran (cas: 205-39-0Electric Literature of C16H10O).
Naphtho[2,1-b]benzofuran (cas: 205-39-0) belongs to benzofurans derivatives. Benzofuran derivatives are one of the most important oxygen-containing heterocycles. As benzofurans are prone to undergo ring opening of the heterocycle, examples of reduction of this type of aromatics by using dissolving metals are rather scarce.Electric Literature of C16H10O
Referemce:
Benzofuran – Wikipedia,
Benzofuran | C8H6O – PubChem