scikit classifier not fitting on model

[james6601]

Hi everyone, I am trying to fit my model with the art.estimators.sklearnclassifer but it only recognises one class label even though i have 2 [0,1]. Can anyone at all help me resolve this issue?

full error with traceback:

Traceback (most recent call last):


  File ~\AppData\Roaming\Python\Python39\site-packages\art\estimators\classification\classifier.py:73 in replacement_function
    return fdict[func_name](self, *args, **kwargs)

  File ~\AppData\Roaming\Python\Python39\site-packages\art\estimators\classification\scikitlearn.py:176 in fit
    self.model.fit(x_preprocessed, y_preprocessed, **kwargs)

  File C:\ProgramData\Anaconda3\lib\site-packages\sklearn\svm\_base.py:199 in fit
    y = self._validate_targets(y)

  File C:\ProgramData\Anaconda3\lib\site-packages\sklearn\svm\_base.py:720 in _validate_targets
    raise ValueError(

ValueError: The number of classes has to be greater than one; got 1 class

EDIT

I have encoded my train labels as well as my test labels and I'm still receiving the error

np.unique(y_train)
Out[3]: array([0, 1])

@beat-buesser can you advise?

[beat-buesser]

Hi @james6601 Is y_trn and y_train the same?

[james6601]

Hi @beat-buesser sorry I changed y_trn to y_train but I'm still receiving the error. Its as if the ART classifier doesnt recognise the different class labels

[beat-buesser]

Are you providing the labels as strings BENIGN and DDoS? If yes, you have to convert it into a one-hot-encoded array.

[james6601]

Hi, @beat-buesser.
Yeah i have one hot encoded the labels aswell as encoding them before hand but now receiving an error saying that axis 1 is out of bounds for dimension 1

[beat-buesser]

Hi @james6601 Can you show more details?