Merge branch 'main' into reduce-proba

docs/source/api_reference/classification.rst

@@ -23,6 +23,17 @@ Composition
     SklearnClassifierPipeline
     MultiplexClassifier
 
+Model selection and tuning
+--------------------------
+
+.. currentmodule:: sktime.classification.model_selection
+
+.. autosummary::
+    :toctree: auto_generated/
+    :template: class.rst
+
+    TSCGridSearchCV
+
 Ensembles
 ---------
 
@@ -182,8 +193,15 @@ Shapelet-based
     MrSEQL
     MrSQM
 
-sklearn
--------
+
+sklearn classifiers
+-------------------
+
+This section contains classifiers which are not time series classifiers but
+simple tabular classifiers in ``sklearn`` compatible API.
+
+They are used internally in time series classifiers, but can also be used
+directly in a tabular setting.
 
 .. currentmodule:: sktime.classification.sklearn
 

sktime/base/_base.py

@@ -622,12 +622,12 @@ def _get_fitted_params_default(self, obj=None):
 
         # default retrieves all self attributes ending in "_"
         # and returns them with keys that have the "_" removed
-        fitted_params = [attr for attr in dir(obj) if attr.endswith("_")]
-        fitted_params = [x for x in fitted_params if not x.startswith("_")]
-        fitted_params = [x for x in fitted_params if hasattr(obj, x)]
-        fitted_param_dict = {p[:-1]: getattr(obj, p) for p in fitted_params}
-
-        return fitted_param_dict
+        fitted_params = {
+            attr[:-1]: getattr(obj, attr)
+            for attr in dir(obj)
+            if attr.endswith("_") and not attr.startswith("_") and hasattr(obj, attr)
+        }
+        return fitted_params
 
     def _get_fitted_params(self):
         """Get fitted parameters.

sktime/classification/model_selection/__init__.py

@@ -0,0 +1,6 @@
+"""Tuning of time series classifiers."""
+# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
+
+from sktime.classification.model_selection._tune import TSCGridSearchCV
+
+__all__ = ["TSCGridSearchCV"]