Machine Learning Models for Soil Properties
Compute Row-wise Means for Groups of Columns
Merge Soil Laboratory Data with Spectral Data
Machine Learning Function for Soil Spectral Data
Compute Model Evaluation Metrics
Aggregate VNIR Spectra by Columns
Soil and Spectral Data Preprocessing for Model Training
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.