title: Dimension error with SMOTE for oversampling
body: <p>I have a quick question on how to use the SMOTE module in the imblearn library for imbalanced dataset: </p>
  
  <p>I have a dataset to train my DNN model. It has 12442 samples and each sample is a 650*5 array:<br>
  X.shape  #  (12442, 650, 5)
  y.shape  #  (12442, 1)</p>
  
  <p>The dataset works well with my DNN model built with tf.keras API. </p>
  
  <p>However when I tried to add over sampling with SMOTE, it returns error: </p>
  
  <pre><code>from imblearn.over_sampling import SMOTE
  sm = SMOTE()
  X, y = sm.fit_sample(X, y)
  
  ValueError: Found array with dim 3. Estimator expected &lt;= 2.
  </code></pre>
  
  <p>Is it that SMOTE in the imblearn package only takes 1d data? Is there a way or another package to get around it?</p>