id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_wqit3j3isractbtv2fgeoweo5y	Terry Harris	Credit scoring using the clustered support vector machine	2015	3	.pdf	application/pdf	1912	144	52	Credit scoring using the clustered support vector machine Credit scoring using the clustered support vector machine This work investigates the practice of credit scoring and introduces the use of the clustered support vector machine (CSVM) for credit scorecard development. non-linear classifiers (e.g. the kernel support vector machine) have classifiers to credit scoring, which are capable of separating nonlinear data while remaining relatively inexpensive computationally, various techniques have been used to build credit scoring applications by credit analyst, researchers, and software developers. techniques have included; discriminant analysis, linear regression, In recent times, the use of more complex non-linear techniques, credit scoring applications has seen significant increases in the both applied Fisher's (1936) discriminant analysis to credit scoring. technique for credit scoring. technique has been frequently applied to build credit scoring Eisenbeis (1978) point-out a number of the statistical problems in applying discriminant analysis to credit scorecard the most commonly used techniques in credit scoring.	./cache/work_wqit3j3isractbtv2fgeoweo5y.pdf	./txt/work_wqit3j3isractbtv2fgeoweo5y.txt