Description Usage Arguments Details Value Author(s)
Internal function to fit mboost model on a subset of the data
1 2 3 | parboost_fit(subsample_indices, data = NULL, path_to_data,
data_import_function, preprocessing, seed, formula, baselearner, family,
control, tree_controls, cv, cores_cv = detectCores(), folds, stepsize_mstop)
|
subsample_indices |
A numeric vector containing the indices of the subsample |
data |
A data frame containing the variables in the model. It is recommended to use path_to_data instead for IO efficiency. Defaults to NULL |
path_to_data |
A string with the path to the data. |
data_import_function |
What function should be used to import the data? |
preprocessing |
Optional preprocessing function to apply to the data passed from parboost |
seed |
Set a seed for reproducible results. |
formula |
Formula for mboost. |
baselearner |
Character string determining the type of base learner. |
family |
mboost family |
control |
mboost control |
tree_controls |
party control |
cv |
Cross-validate? |
cores_cv |
Number of cores to use during cv. |
folds |
Number of folds to use for cv. |
stepsize_mstop |
Stepsize used for optimizing mstop. |
Fits a mboost model on each subset of the data
The fitted submodel and its predictions
Ronert Obst
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