title: norm parameters in sklearn.preprocessing.normalize
body: <p>In <a href="http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html" rel="nofollow noreferrer">sklearn documentation</a> says &quot;norm&quot; can be either</p>
  <blockquote>
  <p>norm : ‘l1’, ‘l2’, or ‘max’, optional (‘l2’ by default)<br />
  The norm to use to normalize each non zero sample (or each non-zero feature if axis is 0).</p>
  </blockquote>
  <p><a href="http://scikit-learn.org/stable/modules/preprocessing.html#preprocessing-normalization" rel="nofollow noreferrer">The documentation about normalization</a> isn't clearly stating how ‘l1’, ‘l2’, or ‘max’ are calculated.</p>
  <p>Can anyone clear these?</p>