title: Use sklearn.neural_network.MLPClassifier with ndarray of csr_matrices
body: <p>So I am facing the following classification problem: I have a lot of different (large) 2d-matrices with many zero-entries (therefore maybe meaningful to use sparse-matrices), which need to be classified.</p>
  <p>I wanted to test sklearn's various classifiers, but they only seem to work with np.ndarrays as X_train data (at least according to <a href="https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html" rel="nofollow noreferrer">the documentation</a>)</p>
  <p>I wanted to do the following (minimal example):</p>
  <pre><code>data=np.ndarray(2);
  data[0] = sparse.csr_matrix((x_d, (x_r, x_c)), shape=(x_size, y_size))
  </code></pre>
  <p>But this gives me the following error:</p>
  <pre><code>ValueError: setting an array element with a sequence.
  </code></pre>
  <p>Any idea how to deal with this? I haven't really found any input on classifying a number of sparse matrices.</p>