aif360.sklearn.utils
.check_inputs
- aif360.sklearn.utils.check_inputs(X, y, sample_weight=None, ensure_2d=True)[source]
Input validation for debiasing algorithms.
Checks all inputs for consistent length, validates shapes (optional for X), and returns an array of all ones if sample_weight is
None
.- Parameters:
X (array-like) – Input data.
y (array-like, shape = (n_samples,)) – Target values.
sample_weight (array-like, optional) – Sample weights.
ensure_2d (bool, optional) – Whether to raise a ValueError if X is not 2D.
- Returns:
tuple – * X (
array-like
) – Validated X. Unchanged.y (
array-like
) – Validated y. Possibly converted to 1D if not apandas.Series
.sample_weight (
array-like
) – Validated sample_weight. If no sample_weight is provided, returns a consistent-length array of ones.