ValueError: Data is not binary and pos_label is not specified

Question

I am trying to calculate roc_auc_score, but I am getting following error.

\"ValueError: Data is not binary and pos_label is not specified\"


        

Answer 1

We have problem in y_true=np.array(['0', '1', '0', '0', '1', '1', '1', '1', '1']) Convert values of y_true to Boolean

y_true= '1' <= y_true
print(y_true) # [False  True False False  True  True  True  True  True]

Answer 2

You only need to change y_trueso it looks like this:

y_true=np.array([0, 1, 0, 0, 1, 1, 1, 1, 1])

Explanation: If you take a look to what roc_auc_score functions does in https://github.com/scikit-learn/scikit-learn/blob/0.15.X/sklearn/metrics/metrics.py you will see that y_true is evaluated as follows:

classes = np.unique(y_true)
if (pos_label is None and not (np.all(classes == [0, 1]) or
 np.all(classes == [-1, 1]) or
 np.all(classes == [0]) or
 np.all(classes == [-1]) or
 np.all(classes == [1]))):
    raise ValueError("Data is not binary and pos_label is not specified")

At the moment of the execution pos_label is None, but as long as your are defining y_true as an array of characters the np.all are always false and as all of them are negated then the if condition is trueand the exception is raised.