CoDaCoRe-Derived Feature Selection — codaFS_codacore

Selects features appearing in sparse CoDaCoRe balances. The official `codacore` backend is used when available and functional; otherwise the existing OmicSelector sparse-balance fallback is reused. Feature scores are aggregated across balances using absolute slopes when available.

Usage

codaFS_codacore_wrapper(
  X,
  y,
  n_features = NULL,
  positive = NULL,
  input_scale = c("log", "raw"),
  backend = c("auto", "official", "fallback"),
  max_balances = NULL,
  top_k = 3L,
  class_weight = FALSE,
  verbose = FALSE,
  seed = 42L
)

Arguments

X: Numeric matrix with samples in rows and features in columns.
y: Binary outcome vector.
n_features: Optional target panel size.
positive: Optional positive-class label for non-numeric outcomes.
input_scale: Either `"log"` (default) or `"raw"`.
backend: One of `"auto"`, `"official"`, or `"fallback"`.
max_balances: Maximum number of balances to extract.
top_k: Initial sparse balance size for the fallback backend.
class_weight: Logical; passed to the fallback backend.
verbose: Logical; print backend messages.
seed: Integer random seed.

Value

A list with per-feature `scores`, `selected_features`, extracted balances, and backend details.