DOC: Updated contributors.md

CONTRIBUTORS.md

@@ -33,8 +33,9 @@ List of Contributors
   - Skipper is the major contributor to the scikit-learn module of xgboost.
 * [Zygmunt Zając](https://github.com/zygmuntz)
   - Zygmunt is the master behind the early stopping feature frequently used by kagglers.
-* [Ajinkya Kale](https://github.com/ajkl)
 * [Yuan Tang](https://github.com/terrytangyuan)
+  - Yuan is the major contributor to unit tests in R and Python. 
+* [Ajinkya Kale](https://github.com/ajkl)
 * [Boliang Chen](https://github.com/cblsjtu)
 * [Vadim Khotilovich](https://github.com/khotilov)
 * [Yangqing Men](https://github.com/yanqingmen)

tests/python/test_early_stopping.py

@@ -1,9 +1,14 @@
 import xgboost as xgb
+from sklearn.datasets import load_digits
+from sklearn.cross_validation import KFold, train_test_split
 
+def test_early_stopping_nonparallel():
+	digits = load_digits(2)
+	X = digits['data']
+	y = digits['target']
+	X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
+	clf = xgb.XGBClassifier()
+	clf.fit(X_train, y_train, early_stopping_rounds=10, eval_metric="auc",
+	        eval_set=[(X_test, y_test)])
 
-X = digits['data']
+# todo: parallel test for early stopping
-y = digits['target']
-X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
-clf = xgb.XGBClassifier()
-clf.fit(X_train, y_train, early_stopping_rounds=10, eval_metric="auc",
-        eval_set=[(X_test, y_test)])