rROC on a matrix of (samples x features)

Usage

# S3 method for class 'matrix'
rROC(x, y, ...)

x

Matrix, rows are samples, columns are features. Every feature should be restricted.

y

Factor vector, values of the dependent variable for every column (element/sample).

...

Arguments passed on to rROC.data.frame

save_path: Path to save the results to. Intermediate results are saved into the directory file.path(save_path, "_partial_directory").
save_intermediate: Should intermediate results be saved to disk? If TRUE, every combination by itself is saved into file.path(save_path, "_partial_directory").
load_existing_intermediate: Should the earlier saved intermediate results in the folder file.path(save_path, "_partial_directory") be loaded?
do_plots: Should the plot_density_rROC_empirical be calculated and returned?
verbose: Should progress be printed?
n_permutations: How many permutations should be done
fix_seed: boolean: If not FALSE, the seed for each permutation will be set by set.seed(fix_seed + permutation_i)
parallel_permutations: boolean: If TRUE, the permutation will be done via future.apply::future_lapply, otherwise by base::lapply
positive_label: Label for the positive class. All other values of response are regarded as negative cases.

A list of lists of simple_rROC_permutation and plot results. It is structured as follows: