plot_results_cv: Plot cross-validated results for the ML model and the trait...

In cjubin/learnMET: Predictions with Machine Learning methods in Multi Environment Trials (MET)

Plot cross-validated results for the ML model and the trait under study.

Description

Prediction accuracy is always computed on an environmental basis (i.e. the correlations between the observed and predicted values are calculated within the same environment, no matter what is the cross-validation scheme used).

Usage

plot_results_cv(
  fitting_all_splits,
  trait,
  info_environments,
  cv_type,
  cv0_type,
  path_folder,
  nb_folds_cv1,
  repeats_cv1,
  nb_folds_cv2,
  repeats_cv2
)

Arguments

fitting_all_splits	results obtained using the function fit_cv_split() for all train/test partitions.
trait	character used in the predict_trait_MET_cv() function called.
info_environments	data.frame used in the predict_trait_MET_cv(). Typically METData$info_environments.
cv_type	character CV type used in the predict_trait_MET_cv() function called.
cv0_type	character For CV0 type, different possibilities are: "leave-one-environment-out", "leave-one-site-out", "leave-one-location-out".
path_folder	character Path where plots should be saved.
nb_folds_cv1	numeric Number of folds used in the CV1 scheme.
repeats_cv1	numeric Number of repeats in the CV1 scheme.
nb_folds_cv2	numeric Number of folds used in the CV2 scheme.
repeats_cv2	numeric Number of repeats in the CV2 scheme.

Value

Plots are directly saved in the path_folder.

Author(s)

Cathy C. Westhues [e-mail]

cjubin/learnMET documentation built on Nov. 4, 2024, 6:23 p.m.