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Explainable Artificial Intelligence Approaches: A Survey
The lack of explainability of a decision from an Artificial Intelligence (AI) based "black box" system/model, despite its superiority in many real-world applications, is a key stumbling block for adopting AI in many high stakes applications of different domain or industry.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction
Although "black box" models such as Artificial Neural Networks, Support Vector Machines, and Ensemble Approaches continue to show superior performance in many disciplines, their adoption in the sensitive disciplines (e. g., finance, healthcare) is questionable due to the lack of interpretability and explainability of the model.
Credit Default Mining Using Combined Machine Learning and Heuristic Approach
Predicting potential credit default accounts in advance is challenging.
Mining Illegal Insider Trading of Stocks: A Proactive Approach
Illegal insider trading of stocks is based on releasing non-public information (e. g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public.
