Kaggle competition: Santander Customer Satisfaction
<choose_model_class><EOS> 
y_train = df_train['TARGET'].values
X_train = df_train.drop(['ID','TARGET'], axis=1 ).values
id_test = df_test['ID']
X_test = df_test.drop(['ID'], axis=1 ).values
len_train = len(X_train)
 len_test = len(X_test)
 clf = xgb.XGBClassifier(missing=np.nan, max_depth=5, n_estimators=350, learning_rate=0.03, nthread=4, subsample=0.95, colsample_bytree=0.85, seed=4242)
 X_fit, X_eval, y_fit, y_eval= train_test_split(X_train, y_train, test_size=0.3)
 clf.fit(X_train, y_train, early_stopping_rounds=20, eval_metric="auc", eval_set=[(X_eval, y_eval)])
 print('Overall AUC:', roc_auc_score(y_train, clf.predict_proba(X_train)[:,1]))
y_pred= clf.predict_proba(X_test)[:,1]
submission = pd.DataFrame({"ID":id_test, "TARGET":y_pred})
 submission.to_csv("submission_2016_03_15.csv", index=False)
 print('Completed!' )