title: Difference between model score() vs r2_score
body: <p>I am training a LinearRegression() classifier and trying to gauge its prediction accruacy</p>
  
  <pre><code>from sklearn.metrics import r2_score
  from sklearn.linear_model import LinearRegression
  regr_rf = LinearRegression()
  
  regr_rf.fit(df[features],df['label'])
  y_rf = regr_rf.predict(df[features])
  score = regr_rf.score(df[features],df['label'])
  print score
  score2 = r2_score(y_rf,df['label'])
  print score2
  </code></pre>
  
  <p>both score and score2 are showing very different value. I though the score function of the model is suppose to be the same as r2_score calculated explicitly </p>