title: Training a SVM on Facial keypoints - how do I cast the features to the correct shape?
body: <p>I'm trying to train a SVM (in python, scikit-learn) to recognize facial expressions.  I've gotten the facial keypoints from a bunch of images, and put them into a list of lists, but this data format isn't correct for a SVM.  </p>
  
  <p>Each of my "training points" is an array of shape (68, 2) corresponding to the coordinates of 68 facial keypoints associated with that image. So my x_train ends up being a 3D array, whereas a SVM requires an array of dimension &lt;= 2.</p>
  
  <p>What's the best approach to restructure this data? I could cast the (68,2) into (136,), but would that preserve my features?  I feel like that would lose the features that I'd like the SVM to be able to classify. </p>
  
  <p>Thanks.</p>