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Bankruptcy prediction and stress quantification using support vector machine : evidence from Indian banks

Shrivastava, Santosh Kumar; Ramudu, P. Janaki - In: Risks : open access journal 8 (2020) 2/52, pp. 1-22

Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...

Persistent link: https://www.econbiz.de/10012292870

Surrogate Data Models : Interpreting Large-Scale Machine Learning Crisis Prediction Models

Chan-Lau, Jorge A.; Hu, Ruofei; Ivanyna, Maksym; Qu, Ritong - 2023

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis...

Persistent link: https://www.econbiz.de/10014256873

Machine learning-based classifiers ensemble for credit risk assessment

Pandey, Trilok Nath; Jagadev, Alok Kumar; Choudhury, D.; … - In: International journal of electronic finance : IJEF 7 (2013) 3/4, pp. 227-249

Persistent link: https://www.econbiz.de/10010400393

Applying machine learning algorithms to determine and predict the reasons and models for employee turnover

Shankar, Shardul; Vyas, Ranjana; Tewari, Vijayshri - In: International journal of information technology and … 23 (2024) 1, pp. 48-63

Persistent link: https://www.econbiz.de/10015064845

Managing uncertainty in ferry terminals : a machine learning approach

Ansorena, Iñigo L.; Lopez Ansorena, César - In: International journal of business information systems : … 33 (2020) 2, pp. 285-297

Persistent link: https://www.econbiz.de/10012172529

When algorithmic predictions use human-generated data : a bias-aware classification algorithm for breast cancer diagnosis

Ahsen, Mehmet Eren; Ayvaci, Mehmet Ulvi Saygi; … - In: Information systems research : ISR 30 (2019) 1, pp. 97-116

Persistent link: https://www.econbiz.de/10012038210

A hybrid classification-based model for automatic text summarisation using machine learning approaches : CBS-ID3MV

Hannah, M. Esther - In: International journal of product development : IJPD 23 (2019) 2/3, pp. 201-211

Persistent link: https://www.econbiz.de/10012105699

Machine learning methods for quality prediction in production

Sankhye, Sidharth; Hu, Guiping - In: Logistics 4 (2020) 4/35, pp. 1-19

production stages. Thus, supervised machine learning methods such as classification can viably predict product compliance quality … manufacturing processes, the adoption of classification methods to predict the overall compliance of production batches has not been … extensively investigated. This paper aims to design machine learning based classification methods for quality compliance and …

Persistent link: https://www.econbiz.de/10012426118

Forecasting consumer credit recovery failure : classification approaches

Kim, Hyeongjun; Cho, Hoon; Ryu, Doojin - In: The journal of credit risk : published quarterly by … 17 (2021) 3, pp. 117-140

Persistent link: https://www.econbiz.de/10012816939

Adversarial robustness for latent models : revisiting the robust-standard accuracies tradeoff

Javanmard, Adel; Mehrabi, Mohammad - In: Operations research 72 (2024) 3, pp. 1016-1030

Persistent link: https://www.econbiz.de/10014557444