imblearn/under_sampling/base.py

Survived

Mutant 349

--- imblearn/under_sampling/base.py
+++ imblearn/under_sampling/base.py
@@ -16,43 +16,7 @@
 
     _sampling_type = "under-sampling"
 
-    _sampling_strategy_docstring = """sampling_strategy : float, str, dict, callable, default='auto'
-        Sampling information to sample the data set.
-
-        - When ``float``, it corresponds to the desired ratio of the number of
-          samples in the minority class over the number of samples in the
-          majority class after resampling. Therefore, the ratio is expressed as
-          :math:`\\alpha_{us} = N_{m} / N_{rM}` where :math:`N_{m}` is the
-          number of samples in the minority class and
-          :math:`N_{rM}` is the number of samples in the majority class
-          after resampling.
-
-          .. warning::
-             ``float`` is only available for **binary** classification. An
-             error is raised for multi-class classification.
-
-        - When ``str``, specify the class targeted by the resampling. The
-          number of samples in the different classes will be equalized.
-          Possible choices are:
-
-            ``'majority'``: resample only the majority class;
-
-            ``'not minority'``: resample all classes but the minority class;
-
-            ``'not majority'``: resample all classes but the majority class;
-
-            ``'all'``: resample all classes;
-
-            ``'auto'``: equivalent to ``'not minority'``.
-
-        - When ``dict``, the keys correspond to the targeted classes. The
-          values correspond to the desired number of samples for each targeted
-          class.
-
-        - When callable, function taking ``y`` and returns a ``dict``. The keys
-          correspond to the targeted classes. The values correspond to the
-          desired number of samples for each class.
-        """.rstrip()
+    _sampling_strategy_docstring = None
 
 
 class BaseCleaningSampler(BaseSampler):

Mutant 350

--- imblearn/under_sampling/base.py
+++ imblearn/under_sampling/base.py
@@ -62,7 +62,7 @@
     instead.
     """
 
-    _sampling_type = "clean-sampling"
+    _sampling_type = "XXclean-samplingXX"
 
     _sampling_strategy_docstring = """sampling_strategy : str, list or callable
         Sampling information to sample the data set.

Mutant 351

--- imblearn/under_sampling/base.py
+++ imblearn/under_sampling/base.py
@@ -62,7 +62,7 @@
     instead.
     """
 
-    _sampling_type = "clean-sampling"
+    _sampling_type = None
 
     _sampling_strategy_docstring = """sampling_strategy : str, list or callable
         Sampling information to sample the data set.

Mutant 352

--- imblearn/under_sampling/base.py
+++ imblearn/under_sampling/base.py
@@ -64,28 +64,5 @@
 
     _sampling_type = "clean-sampling"
 
-    _sampling_strategy_docstring = """sampling_strategy : str, list or callable
-        Sampling information to sample the data set.
+    _sampling_strategy_docstring = None
 
-        - When ``str``, specify the class targeted by the resampling. Note the
-          the number of samples will not be equal in each. Possible choices
-          are:
-
-            ``'majority'``: resample only the majority class;
-
-            ``'not minority'``: resample all classes but the minority class;
-
-            ``'not majority'``: resample all classes but the majority class;
-
-            ``'all'``: resample all classes;
-
-            ``'auto'``: equivalent to ``'not minority'``.
-
-        - When ``list``, the list contains the classes targeted by the
-          resampling.
-
-        - When callable, function taking ``y`` and returns a ``dict``. The keys
-          correspond to the targeted classes. The values correspond to the
-          desired number of samples for each class.
-        """.rstrip()
-