Function classifier_entropy

modAL/uncertainty.py:113–130

Entropy of predictions of the for the provided samples. Args: classifier: The classifier for which the prediction entropy is to be measured. X: The samples for which the prediction entropy is to be measured. **predict_proba_kwargs: Keyword arguments to be passed for

(classifier: BaseEstimator, X: modALinput, **predict_proba_kwargs)

def classifier_entropy(classifier: BaseEstimator, X: modALinput, **predict_proba_kwargs) -> np.ndarray:
    """
    Entropy of predictions of the for the provided samples.

    Args:
        classifier: The classifier for which the prediction entropy is to be measured.
        X: The samples for which the prediction entropy is to be measured.
        **predict_proba_kwargs: Keyword arguments to be passed for the :meth:`predict_proba` of the classifier.

    Returns:
        Entropy of the class probabilities.
    """
    try:
        classwise_uncertainty = classifier.predict_proba(X, **predict_proba_kwargs)
    except NotFittedError:
        return np.zeros(shape=(X.shape[0], ))

    return np.transpose(entropy(np.transpose(classwise_uncertainty)))


def uncertainty_sampling(classifier: BaseEstimator, X: modALinput,