Kernel partial least square regression with high resistance to multiple outliers and bad leverage points on near-infrared spectral data analysis
Multivariate statistical analysis such as partial least square regression (PLSR) is the common data processing technique used to handle high-dimensional data space on near-infrared (NIR) spectral datasets. The PLSR is useful to tackle the multicollinearity and heteroscedasticity problem that can be...
| Main Authors: | , , , , |
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| Format: | Article |
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MDPI AG
2021
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