title: Save MinMaxScaler model in sklearn
body: <p>I'm using the <code>MinMaxScaler</code> model in sklearn to normalize the features of a model.</p>
  
  <pre><code>training_set = np.random.rand(4,4)*10
  training_set
  
         [[ 6.01144787,  0.59753007,  2.0014852 ,  3.45433657],
         [ 6.03041646,  5.15589559,  6.64992437,  2.63440202],
         [ 2.27733136,  9.29927394,  0.03718093,  7.7679183 ],
         [ 9.86934288,  7.59003904,  6.02363739,  2.78294206]]
  
  
  scaler = MinMaxScaler()
  scaler.fit(training_set)    
  scaler.transform(training_set)
  
  
     [[ 0.49184811,  0.        ,  0.29704831,  0.15972182],
     [ 0.4943466 ,  0.52384506,  1.        ,  0.        ],
     [ 0.        ,  1.        ,  0.        ,  1.        ],
     [ 1.        ,  0.80357559,  0.9052909 ,  0.02893534]]
  </code></pre>
  
  <p>Now I want to use the same scaler to normalize the test set:</p>
  
  <pre><code>   [[ 8.31263467,  7.99782295,  0.02031658,  9.43249727],
     [ 1.03761228,  9.53173021,  5.99539478,  4.81456067],
     [ 0.19715961,  5.97702519,  0.53347403,  5.58747666],
     [ 9.67505429,  2.76225253,  7.39944931,  8.46746594]]
  </code></pre>
  
  <p>But I don't want so use the <code>scaler.fit()</code> with the training data all the time. Is there a way to save the scaler and load it later from a different file?    </p>