FIX revert wrong previous fix and make weighted scorer test deterministic

Author: ogrisel

sklearn/metrics/tests/test_score_objects.py

@@ -316,9 +316,9 @@ def test_scorer_sample_weight():
     # get sensible estimators for each metric
     sensible_regr = DummyRegressor(strategy='median')
     sensible_regr.fit(X_train, y_train)
-    sensible_clf = DecisionTreeClassifier()
+    sensible_clf = DecisionTreeClassifier(random_state=0)
     sensible_clf.fit(X_train, y_train)
-    sensible_ml_clf = DecisionTreeClassifier()
+    sensible_ml_clf = DecisionTreeClassifier(random_state=0)
     sensible_ml_clf.fit(X_train, y_ml_train)
     estimator = dict([(name, sensible_regr)
                       for name in REGRESSION_SCORERS] +
@@ -341,7 +341,7 @@ def test_scorer_sample_weight():
                              msg="scorer {0} behaves identically when "
                              "called with sample weights: {1} vs "
                              "{2}".format(name, weighted, unweighted))
-            assert_almost_equal(weighted, ignored, decimal=5,
+            assert_almost_equal(weighted, ignored,
                                 err_msg="scorer {0} behaves differently when "
                                 "ignoring samples and setting sample_weight to"
                                 " 0: {1} vs {2}".format(name, weighted,