title: XGBModel' object has no attribute 'evals_result_'
body: <p>I am trying to use xgboost on a dataset. I have seen the same syntax in various blogs but I am getting an error while calling clf.evals_result()
  here is my code </p>
  
  <pre><code>from xgboost import XGBRegressor as xgb
  from sklearn.metrics import mean_absolute_error as mae
  
  evals_result ={}
  eval_s = [(x, y),(xval,yval)]
  
  clf = xgb(n_estimators=100,learning_rate=0.03,tree_method='gpu_hist',lamda=0.1,eval_metric='mae',eval_set=eval_s,early_stopping_rounds=0,evals_result=evals_result)
  
  clf.fit(x,y) 
  
  r = clf.evals_result()
  </code></pre>
  
  <p>here is error I am receiving</p>
  
  <pre><code>---------------------------------------------------------------------------
  AttributeError                            Traceback (most recent call last)
  &lt;ipython-input-138-2d6867968043&gt; in &lt;module&gt;
        1 
  ----&gt; 2 r = clf.evals_result()
        3 
        4 p = clf.predict(xval)
  
  /opt/conda/lib/python3.6/site-packages/xgboost/sklearn.py in evals_result(self)
      399          'validation_1': {'logloss': ['0.41965', '0.17686']}}
      400         """
  --&gt; 401         if self.evals_result_:
      402             evals_result = self.evals_result_
      403         else:
  
  AttributeError: 'XGBRegressor' object has no attribute 'evals_result_'
  </code></pre>