title: Early stopping with GridSearchCV - use hold-out set of CV for validation
body: <p>I want to employ the <code>early-stopping</code>-option in scikit-learns <code>GridSearchCV</code>-method. An example of this is shown in this SO-<a href="https://stackoverflow.com/questions/42993550/gridsearchcv-xgboost-early-stopping">thread</a>:</p>
  
  <pre><code>import xgboost as xgb
  from sklearn.model_selection import GridSearchCV
  
  trainX= [[1], [2], [3], [4], [5]]
  trainY = [1, 2, 3, 4, 5]
  
  testX = trainX 
  testY = trainY
  
  param_grid = {"subsample" : [0.5, 0.8],
                "n_estimators" : [600]}
  
  fit_params = {"early_stopping_rounds":1,
               "eval_set" : [[testX, testY]]}
  
  
  model = xgb.XGBRegressor()
  gridsearch = GridSearchCV(estimator  = xgb.XGBRegressor(), 
                            param_grid=param_grid,
                            fit_params=fit_params,                          
                            verbose=1,                          
                            cv=2)
  gridsearch.fit(trainX,trainY)
  </code></pre>
  
  <p>However, I would like to use as validation set the hold-out set of the cross-validation process. Is there a way to specify this in <code>GridSearchCV</code>?</p>