CODEWITHSUNDEEP
pythonarraysnumpytensorflowconv-neural-network
saraherceg
saraherceg

Reputation: 341

Error: Setting an array element with a sequence with keras

I am building a CNN and have been getting this error when trying to perform:

from tensorflow.keras import utils
trainY=utils.to_categorical(trainY)

ValueError: setting an array element with a sequence.

My trainY are actually labels, and it looks like this:

labels
array([list(['noise']), list(['noise']), list(['noise', 'point_source']),
       list(['noise']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise']), list(['noise']),
       list(['noise', 'point_source']), list(['noise']),
       list(['noise', 'point_source']), list(['noise', 'point_source']),
       list(['noise']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise']), list(['noise']),

Any suggestions how to fix this? Many thanks!

Upvotes: 0

Views: 74

Answers (1)

Nicolas Gervais
Nicolas Gervais

Reputation: 36624

You can do that with sklearn.preprocessing.MultiLabelBinarizer

import numpy as np

labels = np.array([list(['noise']), list(['noise']), list(['noise', 'point_source']),
       list(['noise']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise']), list(['noise']),
       list(['noise', 'point_source']), list(['noise']),
       list(['noise', 'point_source']), list(['noise', 'point_source']),
       list(['noise']), list(['noise', 'point_source']),
       list(['noise', 'point_source']), list(['noise']), list(['noise'])])

That was what you had. Now you need to do this:

from sklearn.preprocessing import MultiLabelBinarizer

as_list = [list(i) for i in labels]

mlb = MultiLabelBinarizer()
ohe = mlb.fit_transform(as_list) # you might need to add .astype(float)

This is what you'll end up with:

array([[1, 0],
       [1, 0],
       [1, 1],
       [1, 0],
       [1, 1],
       [1, 1],
       [1, 1],
       [1, 1], ...

Upvotes: 1

Related Questions