8e0cb25029e4f1443168adb9313b3f49ae13ea0e,modAL/multilabel.py,,SVM_binary_minimum,#Any#Any#Any#,45

Before Change

    min_abs_dist = np.min(np.abs(decision_function), axis=1)

    if not random_tie_break:
        query_idx = np.argmin(min_abs_dist)
    else:
        query_idx = shuffled_argmax(min_abs_dist)

    return query_idx, X_pool[query_idx]


def max_loss(classifier: OneVsRestClassifier, X_pool: modALinput,
             n_instances: int = 1, random_tie_break: bool = False) -> Tuple[np.ndarray, modALinput]:

After Change

    if not random_tie_break:
        return np.argmin(min_abs_dist)

    return shuffled_argmax(min_abs_dist)


def max_loss(classifier: OneVsRestClassifier, X_pool: modALinput,
             n_instances: int = 1, random_tie_break: bool = False) -> np.ndarray:

Instances