I believe that your current code assumes that the output of sklearn.model.predict() and sklearn.model.predict_proba() are the same. However, they have shapes of (n,) and (n,2) respectively.
In the case of predict_proba(), appending a 2D shape object to a 1 dimensional list causes an error.
I should mention that this error comes up when you fit the training data. The error itself is:
job exception: Found input variables with inconsistent numbers of samples: [number, numberx2]
I believe that your current code assumes that the output of sklearn.model.predict() and sklearn.model.predict_proba() are the same. However, they have shapes of (n,) and (n,2) respectively.
In the case of predict_proba(), appending a 2D shape object to a 1 dimensional list causes an error.
I should mention that this error comes up when you fit the training data. The error itself is: job exception: Found input variables with inconsistent numbers of samples: [number, numberx2]