Update all files to conform to the tidyverse style guide (#6).
All functions renamed to match tidystyle. Old functions names work will be dropped after this version:
AggregateSpectra -> aggregate_spectra()
DoPreprocessing -> pretreat_spectra()
FilterSpectra -> filter_spectra()
FormatCV-> format_cv()
PlotSpectra()-> plot_spectra()
SaveModel()-> save_model()
TestModelPerformance()-> test_spectra()
TrainSpectralModel()-> train_spectra()
"Preprocessing" has been renamed "Pretreatment" to minimize confusion with physical preprocessing of samples prior to scanning. Arguments have been renamed to reflect these changes (preprocessing is now pretreatment).
Added more informative error message and documentation for random forest tune length (tune.length must be set to 5 when model.algorithm == "rf").
Additional flexibility for plot_spectra() including color and title customization and the option to forgo filtering (#5).
Named list output for all functions to enable easier access to individual elements.
Always return model and variable importance results with train_spectra() and test_spectra().
Add variable importance for PLSR (#9).
Enable selection of k for k-fold cross-validation within the training set. Previously, k was fixed at 5 (#10).
save_model() now automatically selects the best model if provided with multiple pretreatments.
Code simplified and streamlined to facilitate future updates.
Export predicted values as well as performance statistics for each training iteration (#11).
wavelengths is no longer a required argument for any of the waves functions.
The proportion of samples to include in the training set can now be selected with the argument proportion.train. Previously, this proportion was fixed at 0.7 (#13).
Bug fix: aggregate_spectra() now allows for aggregation by a single grouping column (#14).
AggregateSpectra->aggregate_spectra()DoPreprocessing->pretreat_spectra()FilterSpectra->filter_spectra()FormatCV->format_cv()PlotSpectra()->plot_spectra()SaveModel()->save_model()TestModelPerformance()->test_spectra()TrainSpectralModel()->train_spectra()preprocessingis nowpretreatment).tune.lengthmust be set to 5 whenmodel.algorithm == "rf").plot_spectra()including color and title customization and the option to forgo filtering (#5).train_spectra()andtest_spectra().save_model()now automatically selects the best model if provided with multiple pretreatments.wavelengthsis no longer a required argument for any of the waves functions.proportion.train. Previously, this proportion was fixed at 0.7 (#13).aggregate_spectra()now allows for aggregation by a single grouping column (#14).