The discovery of experts' decision rules from qualitative bankruptcy data using genetic algorithms
By Myoung-Jong Kim, Ingoo Han. 2003
189 citations recorded by the source corpus.
Subfields: Accounting, Artificial Intelligence, Information Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Yannis Manolopoulos
- Qinghua Huang
- Kai-Yu He
- Efstathios Kirkos
- Berk Ustun
- Hui Li
- Cynthia Rudin
- Jie Sun
In Artificial Intelligence
- Cynthia Rudin
- Berk Ustun
- Yannis Manolopoulos
- Qinghua Huang
- Kai-Yu He
- Efstathios Kirkos
- Hui Li
- Jie Sun
In Information Systems
- Berk Ustun
- Yannis Manolopoulos
- Qinghua Huang
- Kai-Yu He
- Efstathios Kirkos
- Hui Li
- Cynthia Rudin
- Jie Sun
Citations in the corpus
- Supersparse linear integer models for optimized medical scoring systems (2015, background): “ource N P Classication Task adult Kohavi (1996) 32561 36 predict if a U.S. resident earns more than $50000 breastcancer Mangasarian et al. (1995) 683 9 detect breast cancer using a biopsy bankruptcy Kim and Han (2003) 250 6 predict if a rm will go bankrupt haberman Haberman (1976) 306 3 predict 5-ye”
- Data Mining on Finance and Accounting: a Review of Current Research Trends (2004, background): “Kim and Han (2003) built a qualitative model based on experts problem solving knowledge.”
- Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, methodology): “For instance, Jo and Han [52], Jo and Han [53], Park and Han [87], Shin and Lee [106], and Ding et al. [31] selected variables by the statistical methods of stepwise regression or t-test.”
- Big data techniques in auditing research and practice: Current trends and future opportunities (2018, unknown): “Kim (2000) also sees a paradigm shift, with big data offering the opportunity to harvest an ocean of online data, filter information, and generate new knowledge. D. S. Zhang and Zhou (2004) see big data as the way to find the ‘golden nugget’.”