Creates a spectroscopy guideline with a highly accurate prediction model for soil properties using machine learning or deep learning algorithms such as LASSO, Random Forest, Cubist, etc., and decide which algorithm generates the best model for different soil types.
| Version: | 0.1.0 |
| Imports: | gsignal, pls, glmnet, Cubist, randomForest |
| Published: | 2025-10-08 |
| DOI: | 10.32614/CRAN.package.MLSP |
| Author: | Pengyuan Chen [aut, cre], Christopher Clingensmith [aut], Chenglong Ye [aut], Sabine Grunwald [aut], Katsutoshi Mizuta [aut] |
| Maintainer: | Pengyuan Chen <pch276 at uky.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | MLSP results |
| Reference manual: | MLSP.html , MLSP.pdf |
| Package source: | MLSP_0.1.0.tar.gz |
| Windows binaries: | r-devel: MLSP_0.1.0.zip, r-release: MLSP_0.1.0.zip, r-oldrel: MLSP_0.1.0.zip |
| macOS binaries: | r-release (arm64): MLSP_0.1.0.tgz, r-oldrel (arm64): MLSP_0.1.0.tgz, r-release (x86_64): MLSP_0.1.0.tgz, r-oldrel (x86_64): MLSP_0.1.0.tgz |
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