# Multi-label compute class weight - unhashable type

Working in a multi-label classification problem with 13 possibles outputs in my neural network with Keras, sklearn, etc...

Each output can be an array like [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1 ,0].

I have an imbalance dataset and i trying to apply compute_class_weight method, like:

class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)


When i try to run my code, i got Unhashable Type: 'numpy.ndarray':

Traceback (most recent call last):
File "main.py", line 115, in <module>
train(dataset, labels)
File "main.py", line 66, in train
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
File "/home/python-env/env/lib/python3.6/site-packages/sklearn/utils/class_weight.py", line 41, in compute_class_weight
if set(y) - set(classes):
TypeError: unhashable type: 'numpy.ndarray'


I know that is because i working with arrays, already tried add some dict,

i.e.:

class_weight_dict = dict(enumerate(np.unique(y_train), class_weight))


Well, i don't know what to do, tried others strategies, but no success... Any ideas?