Search Results - subject:"interpretability"

Which opinion is more trustworthy : an analysts' earnings forecast quality assessment framework based on machine learning

Song, Yingying; Chen, Xinxin - In: The North American journal of economics and finance : a … 75 (2025) 2, pp. 1-22

Persistent link: https://www.econbiz.de/10015359902

A novel lift adjustment methodology for improving association rule interpretation

Sowan, Bilal; Zhang, Li; Matar, Nasim; Zraqou, J.; … - 2025

mining. More concretely, our main objective is to improve the interpretability of association rules to make them more …

Persistent link: https://www.econbiz.de/10015420467

Forecasting China bond default with severe class-imbalanced data : a simple learning model with causal inference

Peng, Mike W.; Stern, Elisheva R.; Hu, Hanwen - In: Economic modelling 144 (2025), pp. 1-16

Persistent link: https://www.econbiz.de/10015195157

Analyzing decision-making in deep-Q reinforcement learning for trading: A case study on Tesla company and its supply chain

Janda, Karel; Petit, Mathieu - 2024

the interpretability of Q-learning agents. By integrating EV-specific data, such as Tesla's stock fundamentals and key …

Persistent link: https://www.econbiz.de/10015209767

A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis

Zilker, Sandra; Weinzierl, Sven; Kraus, Mathias; … - In: Health Care Management Science 27 (2024) 2, pp. 136-167

Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient’s complete health history to make informed decisions about future events. However, previous work has...

Persistent link: https://www.econbiz.de/10015361777

Multiperiod bankruptcy prediction models with interpretable single models

Beade, Ángel; Rodríguez López, Manuel; Santos, José - In: Computational economics 64 (2024) 3, pp. 1357-1390

Persistent link: https://www.econbiz.de/10015143926

Analyzing decision-making in deep-Q reinforcement learning for trading : a case study on Tesla company and its supply chain

Janda, Karel; Petit, Mathieu - 2024

the interpretability of Q-learning agents. By integrating EV-specific data, such as Tesla's stock fundamentals and key …

Persistent link: https://www.econbiz.de/10015149439

A hybrid multi-criteria decision-making and machine learning approach for explainable supplier selection

Abdulla, Ahmad; Baryannis, George - In: Supply chain analytics 7 (2024), pp. 1-13

Supplier selection has become increasingly complex regarding selection criteria caused by expanded data collection processes and supplier numbers due to globalisation effects. This complexity has led to the consideration of Artificial Intelligence (AI) techniques to facilitate and enhance...

Persistent link: https://www.econbiz.de/10015077540

Headline-driven classification and local interpretation for market outperformance and low-risk stock prediction

Karzanov, Daniil - In: Computational economics 64 (2024) 2, pp. 769-788

Persistent link: https://www.econbiz.de/10015078062

A machine learning framework for interpretable predictions in patient pathways : the case of predicting ICU admission for patients with symptoms of sepsis

Zilker, Sandra; Weinzierl, Sven; Kraus, Mathias; … - In: Health care management science : a new journal serving … 27 (2024) 2, pp. 136-167

Persistent link: https://www.econbiz.de/10015079848