A new fuzzy support vector machine to evaluate credit risk

By Yongqiao Wang, Shouyang Wang, Kin Keung Lai. IEEE transactions on fuzzy systems, 2005

394 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/58e4278f5334845bd2cf57f281f5f13fb59b15e3

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Citations in the corpus

Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, background): “SVM is a powerful and promising data classification and function estimation tool [130], which is not easy to run into over-fitting even for relatively small sample.”
Kernel Methods in Finance (2008, background): “(Wang et al., 2005) proposed fuzzy SVMs to evaluate credit risk.”
Machine Learning in Banking Risk Management: A Literature Review (2019, background): “Wang et al. (2005) propose a new “fuzzy support vector machine”.”
Classification methods applied to credit scoring: A systematic review and overall comparison (2016, background): “Other important comparisons may be seen in Adams et al. (2001); Hoffmann et al. (2002); Ong et al. (2005); Baesens et al. (2005); Wang et al. (2005); Lee et al. (2006); Huang et al. (2006b); Xiao et al. (2006); Van Gestel et al. (2007); Martens et al. (2007); Hu and Ansell (2007); Tsai (2008);…”
FSVM-CIL: Fuzzy Support Vector Machines for Class Imbalance Learning (2010, methodology): “Wang et al. [30] extended this approach by introducing two membership values for each training example, which deﬁne the memberships of both positive and negative classes.”
Credit risk assessment with a multistage neural network ensemble learning approach (2008, methodology): “…credit risk evaluation results with different methodsa Category Model Rule Single LogR ANN SVM Hybrid Neuro-fuzzy (Piramuthu, 1999) Fuzzy SVM (Wang et al., 2005) Ensemble Voting-based Majority Reliability-based Maximum Minimum Median Mean Product a Standard deviations appear in…”
Credit Scoring Models Using Soft Computing Methods: A Survey (2010, background): “[30] Perf Fuzzy-SVM LRA, LOG, MLP, SVM (1) UK corporations Data.”