A Pruning Neural Network Model in Credit Classification Analysis

Table 10

Classification accuracy rates comparison between PNN and other algorithms obtained from the literatures of the Japanese credit dataset.

Authors (published year)	Algorithms (train-to-test ratios)	Classification accuracy rate (%)
Yu et al. (2008) [53]	(10 CV)	75.82
	ANN (10 CV)	80.77
	SVM (10 CV)	79.91
	Neuro-fuzzy hybrid (10 CV)	77.91
	Fuzzy SVM hybrid (10 CV)	83.94
Tsai et al. (2014) [52]	MLP (10 CV)	84.38
Our method (2017)	PNN (50%-50%)	85.54
	PNN (5 CV)	85.23
	PNN (10 CV)	85.27