Principal component analysis: Most favourite tool in chemometrics

被引：0
|
作者：
Kumar K. [1 ]
机构：
[1] Institute for Wine Analysis and Beverage Research, Hochschule, Geisenheim University, Geisenheim
来源：
Resonance | 2017年 / 22卷 / 8期
关键词：
Chemometrics; chromatography; classification; pattern recognition; principal component analysis;
D O I：
10.1007/s12045-017-0523-9
中图分类号：
学科分类号：
摘要：
Principal component analysis (PCA) is the most commonly used chemometric technique. It is an unsupervised pattern recognition technique. PCA has found applications in chemistry, biology, medicine and economics. The present work attempts to understand how PCA work and how can we interpret its results. © 2017, Indian Academy of Sciences.
引用
收藏
页码：747 / 759
页数：12
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