title: Why does creating a custom-sklearn Estimator score go down?
body: <pre><code>from sklearn.base import BaseEstimator
  class random(BaseEstimator):
      def __init__(self):
          self.model=xgboost.XGBClassifier()
      def fit(self,x,y):
          self.model.fit(x,y)
          return self.model
      def predict(self,x):
          return self.model.predict(x)
  rfc=random()
  val=cross_val_score(rfc,train_x_array[:,x.astype(bool)],train_y_array,scoring='accuracy',cv=10,n_jobs=-1)
  val.mean()
  </code></pre>
  
  <blockquote>
    <p>0.7609086695594499</p>
  </blockquote>
  
  <p>score downs??</p>
  
  <pre><code>val=cross_val_score(xgboost.XGBClassifier(),train_x_array[:,x.astype(bool)],train_y_array,scoring='accuracy',cv=10,n_jobs=-1)
  val.mean()
  </code></pre>
  
  <blockquote>
    <p>0.8668378762815749 </p>
  </blockquote>
  
  <p>Is it the BaseEstimator's problem??</p>