A chemometrics toolbox based on projections and latent variables
作者： Lennart Eriksson , Johan Trygg , Svante Wold
DOI: 10.1002/CEM.2581
关键词: Bilinear interpolation 、 Chemometrics 、 Latent variable 、 Principal component analysis 、 Machine learning 、 Toolbox 、 Projection (set theory) 、 Artificial intelligence 、 Mathematics
摘要: A personal view is given about the gradual development of projection methods-also called bilinear, latent variable, and more-and their use in chemometrics. We start with principal components an ...
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