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Projection to latent correlative structures, a dimension reduction strategy for spectral-based classification
Latent variables are used in chemometrics to reduce the dimension of the data. It is a crucial step with spectroscopic data where the number of explanatory variables can be very high. Principal component analysis (PCA) and partial least squares (PLS) are the most common. However, the resulting laten...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society of Chemistry
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040593/ https://www.ncbi.nlm.nih.gov/pubmed/35479572 http://dx.doi.org/10.1039/d1ra03359j |