research.active_learning.random

research.active_learning.random(unlabeled_ids, increment, random_state=None, **kwargs)[source]

Random sample selection.

Parameters
unlabeled_idsarray-like of shape (n_samples,)

Indices of the unlabeled samples in the original (unlabeled training) dataset.

incrementint

Number of observations to select.

random_stateint, RandomState instance, default=None

Control the randomization of the algorithm.

  • If int, random_state is the seed used by the random number generator;

  • If RandomState instance, random_state is the random number generator;

  • If None, the random number generator is the RandomState instance used by np.random.

Returns
new_idsarray of shape (increment,)

Indices of unlabeles samples to be added to the labeled training dataset.