Computes the adjusted score (accuracy, balanced accuracy, etc.) as the maximum
score obtained across all possible permutations of the cluster labels (`y_pred`).
Parameters
----------
y_pred : numpy.ndarray
Predicted cluster labels.
y_true : numpy.ndarray
True class labels.
metric : callable, default=accuracy_score
Function to compute the metric. Must accept (y_true, y_pred) and return a float.
Returns
-------
adj_score : float
The best score obtained across all permutations.
adj_cluster_labels : numpy.ndarray
The cluster labels permuted according to the best permutation.
