title: unable to use FeatureUnion in scikit-learn due to different dimensions
body: <p>I'm trying to use <code>FeatureUnion</code> to extract different features from a datastructure, but it fails due to different dimensions: <code>ValueError: blocks[0,:] has incompatible row dimensions
  </code></p>
  
  <hr>
  
  <h2>Implementaion</h2>
  
  <p>My <code>FeatureUnion</code> is built the following way:</p>
  
  <pre><code>    features = FeatureUnion([
          ('f1', Pipeline([
              ('get', GetItemTransformer('f1')),
              ('transform', vectorizer_f1)
          ])),
          ('f2', Pipeline([
              ('get', GetItemTransformer('f2')),
              ('transform', vectorizer_f1)
          ]))
      ])
  </code></pre>
  
  <p><code>GetItemTransformer</code> is used to get different parts of data out of the same structure. The Idea is described <a href="https://github.com/scikit-learn/scikit-learn/issues/2034#issuecomment-25317009" rel="noreferrer">here</a> in the scikit-learn issue-tracker.</p>
  
  <p>The Structure itself is stored as <code>{'f1': data_f1, 'f2': data_f2}</code> where <code>data_f1</code> are different lists with different lengths.</p>
  
  <hr>
  
  <h2>Question</h2>
  
  <p>Since the Y-Vector is different to the Data-Fields I assume that the error occurs, but how can I scale the vector to fit in both cases?</p>