Remove warnings in tests. (#6554)

tests/python/test_early_stopping.py

@@ -16,7 +16,7 @@ class TestEarlyStopping:
         except ImportError:
             from sklearn.cross_validation import train_test_split
 
-        digits = load_digits(2)
+        digits = load_digits(n_class=2)
         X = digits['data']
         y = digits['target']
         X_train, X_test, y_train, y_test = train_test_split(X, y,
@@ -52,7 +52,7 @@ class TestEarlyStopping:
     def test_cv_early_stopping(self):
         from sklearn.datasets import load_digits
 
-        digits = load_digits(2)
+        digits = load_digits(n_class=2)
         X = digits['data']
         y = digits['target']
         dm = xgb.DMatrix(X, label=y)

tests/python/test_eval_metrics.py

@@ -63,7 +63,7 @@ class TestEvalMetrics:
             from sklearn.cross_validation import train_test_split
         from sklearn.datasets import load_digits
 
-        digits = load_digits(2)
+        digits = load_digits(n_class=2)
         X = digits['data']
         y = digits['target']
 

tests/python/test_training_continuation.py

@@ -2,6 +2,7 @@ import xgboost as xgb
 import testing as tm
 import numpy as np
 import pytest
+import os
 
 rng = np.random.RandomState(1337)
 
@@ -34,8 +35,8 @@ class TestTrainingContinuation:
         from sklearn.datasets import load_digits
         from sklearn.metrics import mean_squared_error
 
-        digits_2class = load_digits(2)
-        digits_5class = load_digits(5)
+        digits_2class = load_digits(n_class=2)
+        digits_5class = load_digits(n_class=5)
 
         X_2class = digits_2class['data']
         y_2class = digits_2class['target']
@@ -85,6 +86,8 @@ class TestTrainingContinuation:
         assert ntrees_03a == 10
         assert ntrees_03b == 10
 
+        os.remove('xgb_tc.model')
+
         res1 = mean_squared_error(y_2class, gbdt_03a.predict(dtrain_2class))
         res2 = mean_squared_error(y_2class, gbdt_03b.predict(dtrain_2class))
         assert res1 == res2