A Novel Ensemble Credit Scoring Model Based on Extreme Learning Machine and Generalized Fuzzy Soft Sets

Algorithm 1

EGHE algorithm.

	Input: Historical data of credit scoring (xi, yi).
	Output: Score of every single customer .
	Step 1. Preprocessing of data.
	Step 2. Variables selection using AEnet.
	Step 3. Imbalanced data rebalancing by using the proposed ensemble strategy.
	Step 4. Credit scoring of every single ELM classifier.
	Step 5. Compute and using (14) and (15).
	Step 6. Calculate the of single classifier using (17).
	Step 7. Calculate the weight of mth classifier using (18).
	Step 8. Get the final credit score of every customer .