title: How to reconstruct raw data from scaled data?
body: <p>I have some data on which I applied scaling with scikit-learn.
  Once scaled I would like to recover the original data.  Is this possible? If not, how can I get correspondance from the original data.</p>
  
  <p>Here a toy example</p>
  
  <pre><code>from sklearn.datasets import load_iris
  from sklearn.preprocessing import scale
  iris = load_iris()
  X = iris.data
  X_scale = scale(X)
  print X[:4]
  print X_scale[:4]
  </code></pre>
  
  <p>producing</p>
  
  <pre><code>[[ 5.1  3.5  1.4  0.2]
   [ 4.9  3.   1.4  0.2]
   [ 4.7  3.2  1.3  0.2]
   [ 4.6  3.1  1.5  0.2]]
  [[-0.90068117  1.03205722 -1.3412724  -1.31297673]
   [-1.14301691 -0.1249576  -1.3412724  -1.31297673]
   [-1.38535265  0.33784833 -1.39813811 -1.31297673]
   [-1.50652052  0.10644536 -1.2844067  -1.31297673]]
  </code></pre>
  
  <p>How from the second data can I recover the original data?</p>