test multioutput for metrics.mean_squared_log_error() (#825)

Author: jameslamb

tests/metrics/test_regression.py

@@ -11,6 +11,7 @@
 
 _METRICS_TO_TEST = [
     "mean_squared_error",
+    "mean_squared_log_error",
     "mean_absolute_error",
     "r2_score",
 ]
@@ -64,18 +65,6 @@ def test_mse_squared(squared):
     assert abs(result - expected) < 1e-5
 
 
-def test_mean_squared_log_error():
-    m1 = dask_ml.metrics.mean_squared_log_error
-    m2 = sklearn.metrics.mean_squared_log_error
-
-    a = da.random.uniform(size=(100,), chunks=(25,))
-    b = da.random.uniform(size=(100,), chunks=(25,))
-
-    result = m1(a, b)
-    expected = m2(a, b)
-    assert abs(result - expected) < 1e-5
-
-
 @pytest.mark.parametrize("multioutput", ["uniform_average", None])
 def test_regression_metrics_unweighted_average_multioutput(metric_pairs, multioutput):
     m1, m2 = metric_pairs