run_regional.mvpa_model | R Documentation |
This function runs a regional MVPA analysis using a specified MVPA model and region mask. The analysis can be customized to return model fits, predictions, and performance measures.
## S3 method for class 'mvpa_model'
run_regional(
model_spec,
region_mask,
return_fits = FALSE,
return_predictions = TRUE,
compute_performance = TRUE,
coalesce_design_vars = FALSE,
...
)
model_spec |
An object of type |
region_mask |
A mask representing different regions in the brain image. |
return_fits |
Whether to return model fit for every ROI (default is |
return_predictions |
Whether to return full prediction table with per trial probabilities (can be a large table, set |
compute_performance |
|
coalesce_design_vars |
Concatenate additional design variables with output stored in 'prediction_table'. |
... |
Additional arguments to be passed to the function. |
A list
of type regional_mvpa_result
containing a named list of NeuroVol
objects,
where each element contains a performance metric and is labeled according to the metric used (e.g. Accuracy, AUC).
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