skactiveml.pool.cost_reduction#
- skactiveml.pool.cost_reduction(k_vec_list, C=None, m_max=2, prior=0.001)[source]#
Calculate the expected cost reduction.
Calculate the expected cost reduction for given maximum number of hypothetically acquired labels, observed labels and cost matrix.
- Parameters
- k_vec_list: array-like, shape (n_samples, n_classes)
Observed class labels.
- C: array-like, shape = (n_classes, n_classes)
Cost matrix.
- m_max: int
Maximal number of hypothetically acquired labels.
- priorfloat | array-like, shape (n_classes)
Prior value for each class.
- Returns
- expected_cost_reduction: array-like, shape (n_samples)
Expected cost reduction for given parameters.