unique_labels#

sklearn.utils.multiclass.unique_labels(*ys)[source]#

Extract an ordered array of unique labels.

We don’t allow:

  • mix of multilabel and multiclass (single label) targets

  • mix of label indicator matrix and anything else, because there are no explicit labels)

  • mix of label indicator matrices of different sizes

  • mix of string and integer labels

At the moment, we also don’t allow “multiclass-multioutput” input type.

Parameters:
*ysarray-likes

Label values.

Returns:
outndarray of shape (n_unique_labels,)

An ordered array of unique labels.

Examples

>>> from sklearn.utils.multiclass import unique_labels
>>> unique_labels([3, 5, 5, 5, 7, 7])
array([3, 5, 7])
>>> unique_labels([1, 2, 3, 4], [2, 2, 3, 4])
array([1, 2, 3, 4])
>>> unique_labels([1, 2, 10], [5, 11])
array([ 1,  2,  5, 10, 11])