Facilitating User Authorization from Imbalanced Data Logs of Credit Cards Using Artificial Intelligence

Algorithm 1

CtRUSBoost (customized RUSBoost).

(i)	Input: , , (with )
(ii)	Output: maximum of [(maximum of value), (maximum of value)]
	Begin
(1)	Initialization of for all
(2)	Do for
(a)	Create temporary training dataset with weight distribution by using random undersampling
(b)	Call decision tree, considering the sample set as and distribution of weight
(c)	Compute a hypothesis
(d)	Call support vector machine considering the sample set as and distribution of weight as
(e)	Compute a hypothesis
(f)	Compute the pseudo loss for SEG and
(g)	Compute the parameter to update the weighing factor:
(h)	Update
(i)	Normalize: Let
(3)	Find the values for and
(a)	For each value of , find out the maximum value of
(b)	For each value of , apply bagging either by performing voting or averaging among all the values of hypothesis obtained
(4)	Compute the final hypothesis as the maximum value between and
	End