A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

Table 4

Logistic regression cross-validation results.

Logistic regression model			Predict value		Hit ratio	Type I error	Type II error
			Non-FFS	FFS
Actual value	CV1	Non-FFS	25	3	80.36%	10.71%	28.57%
		FFS	8	20
	CV2	Non-FFS	26	2	82.14%	7.14%	28.57%
		FFS	8	20
	CV3	Non-FFS	25	3	80.36%	10.71%	28.57%
		FFS	8	20
	Average	Non-FFS	25	3	80.95%	9.52%	28.57%
		FFS	8	20