Hybrid and ensemble-based soft computing techniques in bankruptcy prediction: a survey

167 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Learning for Financial Applications : A Survey (2020, background): “[91] reviewed ML implementations of bankruptcy prediction studies.”
Financial credit risk assessment: a recent review (2015, methodology): “Many researchers have provided the supporting evidences that MCS methodology can produce better performance than individual credit risk assessment models (Deligianni and Kotsiantis 2012; Kuncheva 2004; Rokach 2010; Verikas et al. 2010; Zhou 2012).”
Machine Learning in Financial Crisis Prediction: A Survey (2012, background): “The most recent review [151] presented a comprehensive review of hybrid- and ensemble-based techniques that are used for the prediction of bankruptcy, focusing on the means by which various techniques are combined, rather than the results obtained.”
Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, background): “[125] presented a comprehensive review of hybrid and ensemble-based soft computing techniques for FDP.”