Functional support vector machine.

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Shanghong Xie, R Todd Ogden
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引用次数: 0

Abstract

Linear and generalized linear scalar-on-function modeling have been commonly used to understand the relationship between a scalar response variable (e.g. continuous, binary outcomes) and functional predictors. Such techniques are sensitive to model misspecification when the relationship between the response variable and the functional predictors is complex. On the other hand, support vector machines (SVMs) are among the most robust prediction models but do not take account of the high correlations between repeated measurements and cannot be used for irregular data. In this work, we propose a novel method to integrate functional principal component analysis with SVM techniques for classification and regression to account for the continuous nature of functional data and the nonlinear relationship between the scalar response variable and the functional predictors. We demonstrate the performance of our method through extensive simulation experiments and two real data applications: the classification of alcoholics using electroencephalography signals and the prediction of glucobrassicin concentration using near-infrared reflectance spectroscopy. Our methods especially have more advantages when the measurement errors in functional predictors are relatively large.

功能支持向量机
线性和广义线性标量-函数模型常用于了解标量响应变量(如连续、二元结果)与函数预测因子之间的关系。当响应变量和功能预测因子之间的关系很复杂时,这类技术对模型的错误规范很敏感。另一方面,支持向量机(SVM)是最稳健的预测模型之一,但不能考虑重复测量之间的高度相关性,也不能用于不规则数据。在这项工作中,我们提出了一种新方法,将功能主成分分析与 SVM 分类和回归技术相结合,以考虑功能数据的连续性以及标量响应变量与功能预测因子之间的非线性关系。我们通过大量模拟实验和两个真实数据应用证明了我们方法的性能:利用脑电信号对酗酒者进行分类,以及利用近红外反射光谱预测葡萄糖苷浓度。当功能预测因子的测量误差相对较大时,我们的方法尤其更具优势。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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