支持向量机用户指南。

A user's guide to support vector machines.

作者信息

Ben-Hur Asa, Weston Jason

机构信息

Department of Computer Science, Colorado State University, Fort Collins, CO, USA.

出版信息

Methods Mol Biol. 2010;609:223-39. doi: 10.1007/978-1-60327-241-4_13.

DOI:10.1007/978-1-60327-241-4_13

PMID:20221922

Abstract

The Support Vector Machine (SVM) is a widely used classifier in bioinformatics. Obtaining the best results with SVMs requires an understanding of their workings and the various ways a user can influence their accuracy. We provide the user with a basic understanding of the theory behind SVMs and focus on their use in practice. We describe the effect of the SVM parameters on the resulting classifier, how to select good values for those parameters, data normalization, factors that affect training time, and software for training SVMs.

摘要

支持向量机（SVM）是生物信息学中广泛使用的分类器。要使用支持向量机获得最佳结果，需要了解其工作原理以及用户可以影响其准确性的各种方式。我们向用户提供对支持向量机背后理论的基本理解，并专注于其在实践中的应用。我们描述了支持向量机参数对所得分类器的影响、如何为这些参数选择合适的值、数据归一化、影响训练时间的因素以及用于训练支持向量机的软件。