update version in svdd docs to 1.1, relocate from 1.0 to 1.1 in whats…

…_new add backticks (scikit-learn#20914), deprecate **params in fit (scikit-learn#20843), add feature_names_in_ (scikit-learn#20787)
ivannz · Nov 10, 2021 · 71f8840 · 71f8840
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diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
@@ -1110,13 +1110,6 @@ Changelog
   now deprecated. Use `scipy.sparse.csgraph.shortest_path` instead. :pr:`20531`
   by `Tom Dupre la Tour`_.
 
-:mod:`sklearn.svm`
-..................
-
-- |Feature| Added the :class:`svm.SVDD` class for novelty detection based
-  on soft minimal volume hypersphere around the sample data. :pr:`7910`
-  by :user:`Ivan Nazarov <ivannz>`.
-
 Code and Documentation Contributors
 -----------------------------------
 

diff --git a/doc/whats_new/v1.1.rst b/doc/whats_new/v1.1.rst
@@ -181,6 +181,10 @@ Changelog
   parameters in `fit` instead of `__init__`.
   :pr:`21436` by :user:`Haidar Almubarak <Haidar13 >`.
 
+- |Feature| Added the :class:`svm.SVDD` class for novelty detection based
+  on soft minimal volume hypersphere around the sample data. :pr:`7910`
+  by :user:`Ivan Nazarov <ivannz>`.
+
 :mod:`sklearn.utils`
 ....................
 

diff --git a/sklearn/svm/_classes.py b/sklearn/svm/_classes.py
@@ -1713,7 +1713,7 @@ class SVDD(OutlierMixin, BaseLibSVM):
 
     Read more in the :ref:`User Guide <svm_outlier_detection>`.
 
-    ..versionadded: 1.0
+    ..versionadded: 1.1
 
     Parameters
     ----------
@@ -1788,7 +1788,9 @@ class SVDD(OutlierMixin, BaseLibSVM):
     n_features_in_ : int
         Number of features seen during :term:`fit`.
 
-        .. versionadded:: 0.24
+    feature_names_in_ : ndarray of shape (`n_features_in_`,)
+        Names of features seen during :term:`fit`. Defined only when `X`
+        has feature names that are all strings.
 
     n_support_ : ndarray of shape (n_classes,), dtype=int32
         Number of support vectors for each class.
@@ -1877,8 +1879,8 @@ def fit(self, X, y=None, sample_weight=None, **params):
         Parameters
         ----------
         X : {array-like, sparse matrix} of shape (n_samples, n_features)
-            Set of samples, where n_samples is the number of samples and
-            n_features is the number of features.
+            Set of samples, where `n_samples` is the number of samples and
+            `n_features` is the number of features.
 
         y : Ignored
             Not used, present for API consistency by convention.
@@ -1890,6 +1892,11 @@ def fit(self, X, y=None, sample_weight=None, **params):
         **params : dict
             Additional fit parameters.
 
+            .. deprecated:: 1.0
+                The `fit` method will not longer accept extra keyword
+                parameters in 1.2. These keyword parameters were
+                already discarded.
+
         Returns
         -------
         self : object