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Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design
Åsmund Rinnan,
Lars Munck
4
Citations (Scopus)
11
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Dive into the research topics of 'Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design'. Together they form a unique fingerprint.
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Mathematics
Partial Least Squares Regression
100%
Barley
89%
Experimental design
80%
Human
64%
Prediction
57%
Spectrality
23%
Protein
21%
Biology
20%
Near-infrared Spectroscopy
17%
Chemometrics
14%
Prediction Model
13%
Mutant
12%
Genotype
12%
Biological Systems
11%
Inspection
11%
Chemistry
11%
Calibration
11%
Principal Component Analysis
10%
Industry
10%
Regression Coefficient
10%
Covariates
8%
Knowledge
7%
Model
6%
Framework
5%
Class
3%
Engineering & Materials Science
Design of experiments
66%
Proteins
32%
Near infrared spectroscopy
24%
Chemical analysis
23%
Set theory
22%
Biological systems
20%
Principal component analysis
16%
Calibration
13%
Inspection
13%
Industry
7%
Chemical Compounds
Chemometrics
36%
NIR Spectroscopy
36%
Biological Property
34%
Protein
29%
Industry
26%
Food
25%
Chemistry
20%
Mixture
15%