Ranking-order case-based reasoning for financial distress prediction
148 citations recorded by the source corpus.
Subfields: Accounting, Artificial Intelligence, Computational Theory and Mathematics
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
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Citations in the corpus
- The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification (2014, background): “CBR has been used in important real-world applications [24, 4], but is fundamentally limited, in that it does not learn the underlying complex structure of data in an unsupervised fashion and may not scale to datasets with high-dimensional feature spaces (as discussed in [29]).”
- Interactive and interpretable machine learning models for human machine collaboration (2015, background): “CBR has been used in important real-world applications [91, 19], but it does not learn the underlying complex structure of data in an unsupervised fashion and may not scale to datasets with high-dimensional feature spaces (as discussed in [123]).”
- iForest: Interpreting Random Forests via Visual Analytics (2019, unknown): “This aligns with the analogical decision making process of humans [29, 40], which has been widely adopted in various real-world applications, such as the medical [8] and the financial [33] domains.”
- Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, background): “Lateral dynamic modeling for FDP Sun and Li [115] firstly explored the financial distress concept drift (FDCD) that may behave in two ways: real and virtual, and attempted to treat the virtual one by dynamic FDP modeling using five instance selection methods, namely full memory windowing, no memory ”
- An Analysis of Multi-Criteria Decision Making Methods (2013, unknown): “Li and Sun (2008) provide a new method for predicting financial distress in companies one year prior to actual distress using case-based reasoning (CBR).”