[DOC] Update roadmap.
@@ -70,16 +70,16 @@ the document up to date as we work on these issues.
* document current handling
* column reordering issue :issue:`7242`
- * avoiding unnecessary conversion to ndarray :issue:`12147`
+ * avoiding unnecessary conversion to ndarray |ss| :issue:`12147` |se|
* returning DataFrames from transformers :issue:`5523`
- * getting DataFrames from dataset loaders :issue:`10733`,
+ * getting DataFrames from dataset loaders |ss| :issue:`10733` |se|,
|ss| :issue:`13902` |se|
- * Sparse currently not considered :issue:`12800`
+ * Sparse currently not considered |ss| :issue:`12800` |se|
#. Improved handling of categorical features
* Tree-based models should be able to handle both continuous and categorical
- features :issue:`12866` and :issue:`15550`.
+ features :issue:`12866` and |ss| :issue:`15550` |se|.
* |ss| In dataset loaders :issue:`13902` |se|
* As generic transformers to be used with ColumnTransforms (e.g. ordinal
encoding supervised by correlation with target variable) :issue:`5853`,
@@ -89,7 +89,7 @@ the document up to date as we work on these issues.
#. Improved handling of missing data
* Making sure meta-estimators are lenient towards missing data,
- :issue:`15319`
+ |ss| :issue:`15319` |se|
* Non-trivial imputers |ss| :issue:`11977`, :issue:`12852` |se|
* Learners directly handling missing data |ss| :issue:`13911` |se|
* An amputation sample generator to make parts of a dataset go missing
@@ -125,19 +125,20 @@ the document up to date as we work on these issues.
components
* More flexible estimator checks that do not select by estimator name
- :issue:`6599` :issue:`6715`
- * Example of how to develop an estimator or a meta-estimator, :issue:`14582`
+ |ss| :issue:`6599` |se| :issue:`6715`
+ * Example of how to develop an estimator or a meta-estimator,
+ |ss| :issue:`14582` |se|
* More self-sufficient running of scikit-learn-contrib or a similar resource
#. Support resampling and sample reduction
* Allow subsampling of majority classes (in a pipeline?) :issue:`3855`
- * Implement random forests with resampling :issue:`8732`
+ * Implement random forests with resampling :issue:`13227`
#. Better interfaces for interactive development
- * |ss| __repr__ |se| and HTML visualisations of estimators
- |ss| :issue:`6323` |se| and :pr:`14180`.
+ * |ss| __repr__ and HTML visualisations of estimators
+ :issue:`6323` and :pr:`14180` |se|.
* Include plotting tools, not just as examples. :issue:`9173`
#. Improved tools for model diagnostics and basic inference
@@ -249,7 +250,7 @@ Subpackage-specific goals
* perhaps we want to be able to get back more than multiple metrics
* the handling of random states in CV splitters is a poor design and
contradicts the validation of similar parameters in estimators,
- :issue:`15177`
+ `SLEP011 <https://github.com/scikit-learn/enhancement_proposals/pull/24>`_
* exploit warm-starting and path algorithms so the benefits of `EstimatorCV`
objects can be accessed via `GridSearchCV` and used in Pipelines.
:issue:`1626`
