DOC Minor changes in docs (#400)

Author: chkoar

doc/over_sampling.rst

@@ -60,9 +60,9 @@ for usage example.
 From random over-sampling to SMOTE and ADASYN
 ---------------------------------------------
 
-Apart from the random sampling with replacement, there is two popular methods
-to over-sample minority classes: (i) Synthetic Minority Oversampling Technique
-(SMOTE) and (ii) Adaptive Synthetic (ADASYN) sampling method. These algorithm
+Apart from the random sampling with replacement, there are two popular methods
+to over-sample minority classes: (i) the Synthetic Minority Oversampling Technique
+(SMOTE) and (ii) the Adaptive Synthetic (ADASYN) sampling method. These algorithms
 can be used in the same manner::
 
   >>> from imblearn.over_sampling import SMOTE, ADASYN

imblearn/over_sampling/adasyn.py

@@ -16,10 +16,8 @@
 
 
 class ADASYN(BaseOverSampler):
-    """Perform over-sampling using ADASYN.
-
-    Perform over-sampling using Adaptive Synthetic Sampling Approach for
-    Imbalanced Learning.
+    """Perform over-sampling using Adaptive Synthetic (ADASYN) sampling
+    approach for imbalanced datasets.
 
     Read more in the :ref:`User Guide <smote_adasyn>`.