偏最小二乘回归
校准
主成分回归
主成分分析
近红外光谱
子空间拓扑
数据集
集合(抽象数据类型)
谱线
回归
数学
回归分析
辛烷值
统计
最小二乘函数近似
特征选择
模式识别(心理学)
计算机科学
汽油
人工智能
化学
光学
物理
有机化学
天文
估计员
程序设计语言
标识
DOI:10.1016/s0169-7439(97)00038-5
摘要
Described in this paper are two data sets of near infrared (NIR) spectra that are now available for general use. One data set consists of NIR spectra of 100 wheat samples with known protein and moisture content. The second set contains NIR spectra of 60 gasoline samples with known octane numbers. Results from a recent wavelength selection study using the two data sets are summarized. Other results based on the new regression approach of cyclic subspace regression (CSR) are briefly described. Included in CSR are principal component regression, partial least squares and least squares. An explicit description of calibration and validation samples used in both investigations is provided.
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