R: Robust Aggregative Feature Selection

# Robust Aggregative Feature Selection

## Documentation for package ‘RAFS’ version 0.2.5

- DESCRIPTION file
- Package NEWS

## Help Pages

builtin_dist_funs | All built-in feature dissimilarity functions
compute_fs_results | Compute preliminary feature selection results for RAFS
cor_dist | Feature dissimilarity based on Pearson's Correlation (cor)
create_seeded_folds | Create seeded folds
default_dist_funs | Default feature dissimilarity functions
default_fs_fun | Default (example) feature selection function for RAFS
default_hclust_methods | Default hclust methods
get_rafs_all_reps_from_popcnts | Get all representatives from their popcnts
get_rafs_occurrence_matrix | Get co-occurrence matrix from RAFS results
get_rafs_reps_popcnts | Get representatives' popularity counts (popcnts) from RAFS results
get_rafs_rep_tuples_matrix | Get representatives' tuples' co-representation matrix from RAFS results
get_rafs_rep_tuples_popcnts | Get representatives' tuples' popularity counts (popcnts) from RAFS results
get_rafs_tops_popcnts | Get top popularity counts (popcnts) from FS results
get_rafs_top_reps_from_popcnts | Get top (i.e., most common) representatives from their popcnts
get_rafs_top_rep_tuples_from_popcnts | Get top (i.e., most common) representatives's tuples from their popcnts
get_run_id | Generate CV run identifiers
run_rafs | Robust Aggregative Feature Selection (RAFS)
run_rafs_with_fs_results | Robust Aggregative Feature Selection (RAFS) from feature selection results
stig_dist | Symmetric Target Information Gain (STIG) computed directly
stig_from_ig_dist | Symmetric Target Information Gain (STIG) computed from single Information Gains (IGs)
stig_stable_dist | Symmetric Target Information Gain (STIG) computed directly but with pre-computed 1D conditional entropy (aka stable)
vi_dist | Variation of Information (VI)