CODEWITHSUNDEEP
python-3.xscikit-learn
bigboat
bigboat

Reputation: 299

How to get the row/column labels of a Confusion Matrix from scikit-learn?

How would I confirm the the columns/rows of an outputted Confusion Matrix if I didn't initially specify them when creating the matrix such as in the below code: 

    y_true = ["cat", "ant", "cat", "cat", "ant", "bird"]
    y_pred = ["ant", "ant", "cat", "cat", "ant", "cat"]
    cm=confusion_matrix(y_true, y_pred)

    array([[2, 0, 0],
           [0, 0, 1],
           [1, 0, 2]])

From the docs I know it says If none is given, those that appear at least once in y_true or y_pred are used in sorted order so I would assume the columns/rows would be ("ant", "bird", "cat") but how do I confirm that? I tried something like cm.labels but that doesn't work.

Upvotes: 1

Views: 662

Answers (1)

Jarad
Jarad

Reputation: 18883

In the source code of the confusion_matrix:

if labels is None:
    labels = unique_labels(y_true, y_pred)

What is unique_labels and where is it imported from?

from sklearn.utils.multiclass import unique_labels
unique_labels(y_true, y_pred)

Returns

array(['ant', 'bird', 'cat'],
      dtype='<U4')

unique_labels extracts 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])

Maybe a more intuitive example:

unique_labels(['z', 'x', 'y'], ['a', 'z', 'c'], ['e', 'd', 'y'])

Returns:

array(['a', 'c', 'd', 'e', 'x', 'y', 'z'],
      dtype='<U1')

Upvotes: 1

Related Questions