title: Scikit Learn: RandomForest: clf.predict works with float, but not clf.score
body: <p>I'm working on a classification problem. The labels I am trying to predict:</p>
  
  <pre><code>df3['relevance'].unique()
  array([ 3.  ,  2.5 ,  2.33,  2.67,  2.  ,  1.  ,  1.67,  1.33,  1.25,
          2.75,  1.75,  1.5 ,  2.25])
  </code></pre>
  
  <p>When I call predict using the features I've made, it works OK:</p>
  
  <pre><code>clf = RandomForestClassifier()
  clf.fit(df3[features], df['relevance'])
  pd.crosstab(clf.predict(df3[features]), df3['relevance'])
  </code></pre>
  
  <p>But when I call clf.score:</p>
  
  <pre><code>clf.score(df3['features'], df3['relevance'])
  </code></pre>
  
  <p>I get 
  <code>ValueError</code>: continuous is not supported</p>
  
  <p>Should I be classifying the relevance label I am trying to predict as another data type? Thanks for any help. </p>