23077: Documents numerical_precision in get_params (#378)

howsoai · Mar 4, 2025 · 0e9d682 · 0e9d682
1 parent a4ffc8b
commit 0e9d682
Show file tree

Hide file tree

Showing 2 changed files with 25 additions and 1 deletion.
diff --git a/howso/client/base.py b/howso/client/base.py
@@ -5419,6 +5419,18 @@ def get_params(
         weight_feature : str, optional
             If specified, will find and return the best analyzed hyperparameters
             that were analyzed using this weight feature.
+        numerical_precision : str, optional
+            Sets the preference for performance vs. computational accuracy.
+            Valid values are:
+                - "recompute_precise" : default value, will use fast
+                  computation for finding similar cases but recompute their
+                  exact similarities and influences precisely.
+                - "precise" : will always use high precision computation for
+                  finding similar cases and computing similarities
+                  and influences.
+                - "fast" : will always use a fast approach for all computations
+                  which will use faster, but lower precision
+                  numeric operations.
 
         Returns
         -------

diff --git a/howso/engine/trainee.py b/howso/engine/trainee.py
@@ -3453,7 +3453,19 @@ def get_params(
             that were computed in this mode.
         weight_feature : str, optional
             If specified, will find and return the best analyzed hyperparameters
-            that were analyzed using this weight feaure.
+            that were analyzed using this weight feature.
+        numerical_precision : str, optional
+            Sets the preference for performance vs. computational accuracy.
+            Valid values are:
+                - "recompute_precise" : default value, will use fast
+                  computation for finding similar cases but recompute their
+                  exact similarities and influences precisely.
+                - "precise" : will always use high precision computation for
+                  finding similar cases and computing similarities
+                  and influences.
+                - "fast" : will always use a fast approach for all computations
+                  which will use faster, but lower precision
+                  numeric operations.
 
         Returns
         -------