AWSMOTE: An SVM-Based Adaptive Weighted SMOTE for Class-Imbalance Learning

Algorithm 1

AWSMOTE.

Input: majority class , minority class , nearest neighbor , , and
	Output: a new minority class
(1)A set of resamples from and are used to train SVM classifier and obtain the vector of variable weights
(2)Calculate the vector of each minority case weight :
(3)for to do
(4) Count the number of samples generated for each minority case :
(5) for to do
(6)  Compute the nearest neighbors of , obtain ;
(7)  for to do
(8)   The element of variable of the new sample :
	Where is a random number
(9)	end for
(10) end for
(11) Add all the samples generated by to the generated minority class
(12)end for
(13)
(14)return A new minority class