4.7 Article

Towards better understanding of feature-selection or reduction techniques for Quantitative Structure-Activity Relationship models

期刊

TRAC-TRENDS IN ANALYTICAL CHEMISTRY
卷 42, 期 -, 页码 49-63

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2012.09.008

关键词

Aldose-reductase inhibitor; Biological activity; Biological property; Feature reduction; Feature selection; Molecular descriptor; Multiple Linear Regression (MLR); Partial Least Squares (PLS); Quantitative Structure-Activity Relationship (QSAR); Rho kinase (ROCK) inhibitor

资金

  1. Institute of Chemistry Timisoara of the Romanian Academy [1.1]

向作者/读者索取更多资源

A Quantitative Structure-Activity Relationship (QSAR) is a linear or non-linear model, which relates variations in molecular descriptors to variations in the biological activity of a series of active and/or inactive molecules. For this article, different feature-selection or reduction methods were all coupled with Partial Least Squares (PLS) modeling during the selection of features. A PLS model was also built with the entire set of molecular descriptors and was used as a reference to check the reliability and the performance of the different feature-selection methods. To evaluate the ability of the different feature-selection methods, they were performed on two data sets. (c) 2012 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据