A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines

By Tian-Shyug Lee, I-Fei Chen. Expert systems with applications, 2005

414 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/45539f44424577819d351611cd89e4c0f6c1fbad

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Citations in the corpus

Classification methods applied to credit scoring: A systematic review and overall comparison (2016, methodology): “…algorithm and support vector machine to perform feature selection and model parameters optimisation simultaneously, as well as Lee et al. (2002); Lee and Chen (2005); Hsieh (2005); Huysmans et al. (2006); Shi (2009); Chen et al. (2009); Liu et al. (2010); Ping and Yongheng (2011); Capotorti and…”
Predicting Credit Risk in Peer-to-Peer Lending: A Neural Network Approach (2015, background): “The output layer transmits the information outside the network as the target output ,which corresponds to a dependent variable in the data [18,21].”
Credit Scoring, Statistical Techniques and Evaluation Criteria: A Review of the Literature (2011, methodology): “Meanwhile, comparisons between traditional and advanced statistical techniques have been investigated too (Abdou & Pointon, 2009; Abdou et al. 2009; Lee & Chen 2005; Ong et al, 2005; Zekic-Susac et al, 2004; Malhotra & Malhotra, 2003; Lee et al, 2002; Fritz & Hosemann, 2000).”
A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010, methodology): “To build the credit scoring model, at the first, they used MARS and afterward they used the obtained significant variables as the input nodes of the NN models.”
Cluster-based under-sampling approaches for imbalanced data distributions (2009, methodology): “Many studies (Japkowicz, 2001; Lee & Chen, 2005; Li et al., 2004) focused on improving the clas-siﬁcation accuracy but did not consider the imbalanced class distribution problem.”
Artificial neural networks in business: Two decades of research (2016, background): “Throughout the investigated period authors have applied artificial neural networks to various problems including credit scoring [161, 258, 259], financial analysis [52, 186], or stock performance prediction [89, 162, 166].”