View source: R/approach_regression_separate.R
regression.train_model | R Documentation |
Function that trains a tidymodels
model via workflows
based on the provided input parameters.
This function allows for cross validating the hyperparameters of the model.
regression.train_model(
x,
seed = 1,
verbose = 0,
regression.model = parsnip::linear_reg(),
regression.tune = FALSE,
regression.tune_values = NULL,
regression.vfold_cv_para = NULL,
regression.recipe_func = NULL,
regression.response_var = "y_hat",
regression.surrogate_n_comb = NULL
)
x |
Data.table containing the data. Either the training data or the explicands. If |
seed |
Positive integer.
Specifies the seed before any randomness based code is being run.
If |
verbose |
An integer specifying the level of verbosity. If |
regression.model |
A |
regression.tune |
Logical (default is |
regression.tune_values |
Either |
regression.vfold_cv_para |
Either |
regression.recipe_func |
Either |
regression.response_var |
String (default is |
regression.surrogate_n_comb |
Integer (default is |
A trained tidymodels
model based on the provided input parameters.
Lars Henry Berge Olsen
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