mvpa_iterate | R Documentation |
mvpa_iterate(
mod_spec,
vox_list,
ids = 1:length(vox_list),
compute_performance = TRUE,
return_predictions = TRUE,
return_fits = FALSE,
batch_size = as.integer(0.1 * length(ids)),
permute = FALSE,
verbose = TRUE
)
mod_spec |
An object of class |
vox_list |
A |
ids |
A |
compute_performance |
A |
return_predictions |
A |
return_fits |
A |
batch_size |
An permuteA verboseA |
A data.frame
containing the results for each voxel set, including performance measures, predictions, and model fits, as specified by the input parameters.
This function fits a classification or regression model for each voxel set in a list using parallelization.
It can compute and store performance measures, return row-wise predictions, and return the model fit for each voxel set.
This function utilizes parallel processing to speed up the process of fitting the specified model for each voxel set in a list.
The parallelization is achieved using the 'furrr' package, which provides a parallel backend for the 'purrr' package.
By default, it divides the voxel sets into batches and processes them in parallel according to the specified batch size.
The function provides options to control the return of performance measures, predictions, and model fits for each voxel set.
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