title: Sklearn error: 'SVR' object has no attribute '_impl'
body: <p>What I'm doing:
  I am trying to forecast data using a tested (pickled) SVM regression model that was built on another machine. The scaling works fine, but even trying to forecast based on the original learning sample fails with the same error.</p>
  
  <blockquote>
    <p>'SVR' object has no attribute '_impl'</p>
  </blockquote>
  
  <p>The error occurs on a WIN 7 64bit workstation with Python 2.7.5, Numpy 1.7.1 (MKL) and sklearn (scikit-learn 0.14.1). Both are 64bit.</p>
  
  <p>EDIT:</p>
  
  <p>Below is the code. And it worked on the machine that did the learning bit.</p>
  
  <pre><code>from sklearn.svm import SVR
  from sklearn import preprocessing
  import cPickle as cp
  import numpy as np
  model = cp.load(open('model.pkl', 'rb'))
  scaler = cp.load(open('scaler.pkl', 'rb'))
  theData = np.genfromtxt(open('inputData.csv','rb'), delimiter=',')
  scaledXs = scaler.transform( theData )
  result = model.predict( scaledXs )
  </code></pre>
  
  <p>EDIT 2:
  FYI: The learning part was done on piCloud which uses the 0.13.1 version. Could that be the issue?</p>