Performs bootstrap-based feature selection in parallel.
Usage
parallel_bootstrap_features(
data,
n_bootstrap = 1000,
n_workers = NULL,
p_threshold = 0.05,
progress = TRUE
)
Arguments
- data
Data frame with cluster variable in first column.
- n_bootstrap
Number of bootstrap iterations (default: 1000).
- n_workers
Number of workers (default: auto).
- p_threshold
P-value threshold (default: 0.05).
- progress
Show progress (default: TRUE).
Value
List of significant features per cluster.