DOC Add explanation of why iterative imputer is experimental
@@ -105,9 +105,12 @@ imputation round are returned.
.. note::
- This estimator is still **experimental** for now: the predictions
- and the API might change without any deprecation cycle. To use it,
- you need to explicitly import ``enable_iterative_imputer``.
+ This estimator is still **experimental** for now: default parameters or
+ details of behaviour might change without any deprecation cycle. Resolving
+ the following issues would help stabilize :class:`IterativeImputer`:
+ convergence criteria (:issue:`14338`), default estimators (:issue:`13286`),
+ and use of random state (:issue:`15611`). To use it, you need to explicitly
+ import ``enable_iterative_imputer``.
::
@@ -310,4 +313,3 @@ wrap this in a :class:`Pipeline` with a classifier (e.g., a
>>> results = clf.predict(X_test)
>>> results.shape
(100,)
-
