mcmodels.models.homogeneous.forward_subset_selection_conditioning

mcmodels.models.homogeneous.forward_subset_selection_conditioning(X, kappa=1000, random_state=None)

Conditioning through subselecting columns of X.

Randomly select initial column of X, then greedily add columns that minimially increase the conditioning.

Parameters:

X : array, shape (n_samples, n_features)

Array whose columns we wish to subset.

kappa : float, optional, default: 1000

The maximum condition number desired.

Returns:

C : array, shape (n_samples, ?)

Array with condition number < kappa, containing the lesser linearly dependent columns of X.