Confusion-matrix clarification from Python

Question

confusion_matrix(y_test1, pred)
That is my codes 

Confusion matrix, without normalization
True     [[724258    438]
value    [ 25396    302]]
          Predicted value

I understand that is how this is the confusion matrix. But I do not know the order of classification result.

0   [[724258    438]                1 [[724258    438]
1   [ 25396    302]]                0 [ 25396    302]]
       0         1                        1        0

Which order generally? I check the documentation, it does not tell me the specific result.

Answer 1

it's the first one

0   [[724258    438]       
1   [ 25396    302]]      
       0         1  

According to the documentation

sklearn.metrics.confusion_matrix(y_true, y_pred, labels=None, sample_weight=None) 

labels : array, shape = [n_classes], optional List of labels to index the matrix. This may be used to reorder or select a subset of labels. If none is given, those that appear at least once in y_true or y_pred are used in sorted order.