However, instead of one, we have multiple features for each type. Let x i be the array for the chemical properties, and similarly z i stands for the contributions from the graphical/structural properties of the i-th molecule. The proposed model is structured to flexibly model the nonlinear effect of the features, and in addition, respects the presence of two data types. Specifically, we generalize the above linear characterization and specify u i as a nonlinear unknown function of the observed chemical features, f (x i ), and similarly, v i as g(z i ), another unknown nonlinear function of the graphical properties. We call u i and v i as pseudo chemical and graphical features, respectively. This characterization thus also helps to associate the observed chemical and graphical features nonlinearly with solubility. Consequently, the above model then becomes,