Research on Credit Risk Prediction under Unbalanced Dataset Based on Ensemble Learning

Algorithm 2

Random subspace algorithm.

	Input: dataset X = {x1, x2, …, xn|, i = 1, 2, …, n}
	Output: generated q random subspaces S^1, S^2, …, S^n
(1)	Data initialization. Initialize the number n of random subspaces, the dimension of random subspace .
(2)	For the variable features in the dataset, we used a random function to extract p features among them to obtain a random subspace, and we repeated this extraction process n time to obtain n random subspaces.
(3)	Returning generated q random subspaces S^1, S^2, …, S^n.