deephyper.ensemble.aggregator.MixedCategoricalAggregator#
- class deephyper.ensemble.aggregator.MixedCategoricalAggregator(uncertainty_method='confidence', decomposed_uncertainty: bool = False)[source]#
Bases:
Aggregator
Aggregate a set of categorical distributions.
Array (Fixed Set)
MaskedArray
✅
❌
- Parameters:
uncertainty_method (str, optional) –
Method to compute the uncertainty. Can be either
"confidence"
or"entropy"
. Default is"confidence"
."confidence"
: The uncertainty is computed as1 - max(probability)
of the aggregated categorical distribution of ensemble."entropy"
: The uncertainty is computed as theentropy
of of the aggregated categorical distribution of ensemble.
decomposed_uncertainty (bool, optional) – If
True
, the uncertainty of the ensemble is decomposed into aleatoric and epistemic components. Default isFalse
.
Methods
Aggregate the predictions using the mode of categorical distribution.
- aggregate(y: List, weights: List = None)[source]#
Aggregate the predictions using the mode of categorical distribution.
- Parameters:
y (np.array) – Predictions array of shape
(n_predictors, n_samples, n_outputs)
.weights (list, optional) – Weights of the predictors. Default is
None
.
- Returns:
Aggregated predictions of shape
(n_samples, n_outputs)
.- Return type:
np.array