Local partial least squares based on global PLS scores
A local‐based method for near‐infrared spectroscopy predictions, the local partial least squares regression on global PLS scores (LPLS‐S), is proposed in this work and compared with the usual local PLS (LPLS) regression approach. LPLS‐S is based on the idea of replacing the original spectra with a g...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Wiley
2019
|
| Online Access: | https://hdl.handle.net/10568/100718 |
Similar Items: Local partial least squares based on global PLS scores
- Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
- Squaring the circle
- Flex square
- NIRS calibration database on fresh cassava puree to predict cooking time
- NIRS Database on fresh blended cassava for Dry Matter, Water absorption, Texture & cooking Time at CIAT, Colombia
- Towards FAIR and SQUARE hydrological data. Editorial