Python MLPClassifier Value Error
Your data does not make any sense from scikit-learn perspective of what is expected in the .fit call. Feature vectors is supposed to be a matrix of size N x d, where N - number of data points and d number of features, and your second variable should hold labels, thus it should be vector of length N (or N x k where k is number of outputs/labels per point). Whatever is represented in your variables - their sizes do not match what they should represent.
I'm currently trying to train the MLPClassifier implemented in sklearn...
When i try to train it with the given values i get this error:
ValueError: setting an array element with a sequence.
The format of the feature_vector is 
[ [one_hot_encoded brandname], [different apps scaled to mean 0 and variance 1] ]
Does anybody know what I'm doing wrong ?
Thank you!



feature_vectors: 
[
array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.]),
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       -0.22976818, -0.22976818, -0.22976818, -0.22976818, -0.22976818])
]
g_a_group: 
[ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  1.  0.]



MLP:
from sklearn.neural_network import MLPClassifier
clf = MLPClassifier(solver='lbfgs', alpha=1e-5,
                   hidden_layer_sizes=(5, 2), random_state=1)
clf.fit(feature_vectors, g_a_group)