DOC: Fix the documentation of sampling_strategy as a float (#480)

Author: glemaitre

doc/whats_new/v0.0.4.rst

@@ -117,6 +117,10 @@ Documentation
 - Remove some docstring which are not necessary.
   :issue:`454` by :user:`Guillaume Lemaitre <glemaitre>`.
 
+- Fix the documentation of the ``sampling_strategy`` parameters when used as a
+  float.
+  :issue:`480` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 Deprecation
 ...........
 

imblearn/over_sampling/base.py

@@ -21,11 +21,13 @@ class BaseOverSampler(BaseSampler):
         """sampling_strategy : float, str, dict or callable, (default='auto')
         Sampling information to resample the data set.
 
-        - When ``float``, it corresponds to the ratio :math:`\\alpha_{os}`
-          defined by :math:`N_{rm} = \\alpha_{os} \\times N_{m}` where
-          :math:`N_{rm}` and :math:`N_{M}` are the number of samples in the
-          minority class after resampling and the number of samples in the
-          majority class, respectively.
+        - When ``float``, it corresponds to the desired ratio of the number of
+          samples in the majority class over the number of samples in the
+          minority class after resampling. Therefore, the ratio is expressed as
+          :math:`\\alpha_{os} = N_{M} / N_{rm}` where :math:`N_{rm}` and
+          :math:`N_{M}` are the number of samples in the minority class after
+          resampling and the number of samples in the majority class,
+          respectively.
 
             .. warning::
                ``float`` is only available for **binary** classification. An

imblearn/under_sampling/base.py

@@ -19,11 +19,13 @@ class BaseUnderSampler(BaseSampler):
         """sampling_strategy : float, str, dict, callable, (default='auto')
         Sampling information to sample the data set.
 
-        - When ``float``, it corresponds to the ratio :math:`\\alpha_{us}`
-          defined by :math:`N_{rM} = \\alpha_{us} \\times N_{m}` where
-          :math:`N_{rM}` and :math:`N_{m}` are the number of samples in the
-          majority class after resampling and the number of samples in the
-          minority class, respectively.
+        - When ``float``, it corresponds to the desired ratio of the number of
+          samples in the majority class over the number of samples in the
+          minority class after resampling. Therefore, the ratio is expressed as
+          :math:`\\alpha_{us} = N_{rM} / N_{m}` where :math:`N_{rM}` and
+          :math:`N_{m}` are the number of samples in the majority class after
+          resampling and the number of samples in the minority class,
+          respectively.
 
           .. warning::
              ``float`` is only available for **binary** classification. An