Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

<div>Results of predicting the values of the <i>d</i> descriptor, based on a series of <i>d</i>(<i>b</i>, <i>i</i>) MARSplines models characterized by number of initial basis functions (<i>b</i>) and allowed maximum interactions (<i>i</i>). Provided numbers represent amounts of factors used in the final regression function with statistically significant contributions. Grey lines represent results obtained after normalization of each of the descriptor distributions, while black lines correspond to models built on absolute values of descriptors.</div>

Journal of Chemistry

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Figure 1: Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String 

Figure 1 | Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String 