nmr_data_analysis_method: Create method for NMR data analysis
In AlpsNMR: Automated spectraL Processing System for NMR

Description Usage Arguments Value Examples

Create method for NMR data analysis

new_nmr_data_analysis_method(
  train_evaluate_model,
  train_evaluate_model_params_inner,
  choose_best_inner,
  train_evaluate_model_params_outer,
  train_evaluate_model_digest_outer
)

`train_evaluate_model`	A function. The `train_evaluate_model` must have the following signature: function(x_train, y_train, identity_train, x_test, y_test, identity_test, ...) The `x_train` and `y_train` (and their test counterparts) are self-explanatory. The `identity_` arguments are expected to be factors. They can be used for instance with a callback that uses mixOmics::plsda in a `multilevel` approach for longitudinal studies. In those studies the `identity` would be an identifier of the subject. The `...` arguments are free to be defined for each `train_evaluate_model`.
`train_evaluate_model_params_inner, train_evaluate_model_params_outer`	A list with additional arguments to pass to `train_evaluate_model` either in the inner cv loop or in the outer cv loop.
`choose_best_inner`	A function with a single argument: function(inner_cv_results) The argument is a list of `train_evaluate_model` outputs. The return value of must be a list with at least an element named `train_evaluate_model_args`. `train_evaluate_model_args` must be a named list. Each element must be named as one of the `train_evaluate_model` arguments. Each element must be a vector as long as the number of outer cross-validations. The values of each vector must be the values that the `train_evaluate_model` argument must take on each outer cross-validation iteration Additional list elements can be returned and will be given back to the user
`train_evaluate_model_digest_outer`	A function with a single argument: function(outer_cv_results) The argument is a list of `train_evaluate_model` outputs in outer cross-validation. The return value is returned by `nmr_data_analysis`