Fix glossary issues.

cmarmo · cmarmo · commit bdd700f9a48b · 2019-09-17T14:45:58.000+02:00
diff --git a/doc/glossary.rst b/doc/glossary.rst
@@ -1550,6 +1550,8 @@ functions or non-estimator constructors.
     ``pos_label``
         Value with which positive labels must be encoded in binary
         classification problems in which the positive class is not assumed.
+        This value is typically required to compute asymmetric evaluation
+        metrics such as precision and recall.
 
     ``random_state``
         Whenever randomization is part of a Scikit-learn algorithm, a
@@ -1639,15 +1641,6 @@ functions or non-estimator constructors.
         full dataset. For classification, all data in a sequence of
         ``warm_start`` calls to ``fit`` must include samples from each class.
 
-    ``working_memory``
-
-        The optimal size of temporary arrays used by some algoritms.
-        Some calculations when implemented using standard numpy vectorized
-        operations involve using a large amount of temporary memory.
-        Where computations can be performed in fixed-memory chunks the user is
-        allowed to hint at the maximum size of this working memory (defaulting
-        to 1GB). 
-
 .. _glossary_attributes:
 
 Attributes
diff --git a/doc/modules/computing.rst b/doc/modules/computing.rst
@@ -565,7 +565,7 @@ These environment variables should be set before importing scikit-learn.
 
 :SKLEARN_WORKING_MEMORY:
 
-    Sets the default value for the :term:`working_memory` argument of
+    Sets the default value for the `working_memory` argument of
     :func:`sklearn.set_config`.
 
 :SKLEARN_SEED:
