MNT replace log with log1p (#11424)

meetnaren · jnothman · commit 6f9a8dfd54bb · 2018-07-05T09:13:48.000+10:00
diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
@@ -176,7 +176,7 @@ Here is an example of building custom scorers, and of using the
     >>> import numpy as np
     >>> def my_custom_loss_func(y_true, y_pred):
     ...     diff = np.abs(y_true - y_pred).max()
-    ...     return np.log(1 + diff)
+    ...     return np.log1p(diff)
     ...
     >>> # score will negate the return value of my_custom_loss_func,
     >>> # which will be np.log(2), 0.693, given the values for X
diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
@@ -314,7 +314,7 @@ def mean_squared_log_error(y_true, y_pred,
         raise ValueError("Mean Squared Logarithmic Error cannot be used when "
                          "targets contain negative values.")
 
-    return mean_squared_error(np.log(y_true + 1), np.log(y_pred + 1),
+    return mean_squared_error(np.log1p(y_true), np.log1p(y_pred),
                               sample_weight, multioutput)
 
 
