confusion_matrix - too many values to unpack

Question

I'm trying to use the confusion_matrix function, as follows:

tn, fp, fn, tp = confusion_matrix(y_true, y_predict).ravel()

y_true and y_predict are both lists. When I return their shape, I get: (71,).

I'm however getting the following error for the above statement:

ValueError: too many values to unpack

I'm not sure if it is because of the second (empty) dimension in (71,)? I'm not sure how to remove it if it is the issue here.

Any thoughts?

Thanks.

Answer 1

You can only assign multiple variables dynamically if the number of outputs is certain. If you assign the result of confusion_matrix to a single variable, you can then check its contents in a loop and assign the contents conditionally:

returned = confusion_matrix(y_true, y_predict).ravel()

for var in returned:
    #... do stuff with each item in the returned collection

You could also just check its length and if it is 4, you can proceed as usual:

if len(returned) == 4:
    tn, fp, fn, tp = returned

Answer 2

The line you're trying to execute tn, fp, fn, tp = confusion_matrix(y_true, y_predict).ravel() is valid only if you have 2 classes in output (binary classification). However, the error you get is an indicator that you have more than 2 classes (multi-class classification). In this case, there's no meaning of tn, fp, fn, tp. Instead you can visualize the confusion matrix (e.g. by using heatmap).