Support vector machines for the estimation of aqueous solubility

被引：72

作者：

Lind, P ^{[1
]}

Maltseva, T ^{[1
]}

机构：

[1] Medivir AB, S-14144 Huddinge, Sweden

来源：

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES | 2003年 / 43卷 / 06期

关键词：

D O I：

10.1021/ci034107s

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Support Vector Machines (SVMs) are used to estimate aqueous solubility of organic compounds. A SVM equipped with a Tanimoto similarity kernel estimates solubility with accuracy comparable to results from other reported methods where the same data sets have been studied. Complete cross-validation on a diverse data set resulted in a root-mean-squared error = 0.62 and R-2 = 0.88. The data input to the machine is in the form of molecular fingerprints. No physical parameters are explicitly involved in calculations.

引用

页码：1855 / 1859

页数：5

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