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Your neural net architecture is OK. This behavior is a result of inner data checking procedure performed by vecstack. Such behavior is expected because according to scikit-learn convention input arrays should be 2-dimensional.
Of course it would be nice to have ability to stack some convolutional nets. So I created a workaround which makes it possible to pass N-dimensional arrays. It is available only in functional API (i.e. vecstack.stacking function).
You can reinstall patched version directly from github branch:
use pip3 for Python 3
remove --user option if vecstack was installed for all users
Hi,
I tried to do stacking by using kerasClassifier with a cnn but i get this error
ValueError: Found array with dim 4. Estimator expected <= 2.
This is my code for the cnn
`def model1():
model = Sequential()
model.add(Conv2D(16, (3, 3), activation='relu', padding="same", input_shape=(train_files.shape[1:])))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
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