Search Results - subject:"data balancing"

An integrated oversampling and noise reduction method for robust predictive analytics

Lee, Jeong-Wook; Jeon, Young Eun; Seo, Jung-In - 2025

Imbalanced data is often encountered in scenarios where rare but critical events occur much less frequently than others, and it is particularly prominent in fields such as disease diagnosis, fraud detection, and risk management. The main problem with imbalanced data is that predictive models...

Persistent link: https://www.econbiz.de/10015506752

Machine learning and data balancing methods for bankruptcy prediction

Liashenko, Olena; Kravets, Tetyana; Kostovetskyi, Yevhenii - In: Ekonomika 102 (2023) 2, pp. 28-46

compared, in particular, data balancing methods. Nine machine learning algorithms are implemented, in addition five data … balancing methods (random oversampling, SMOTE, ADASYN, random undersampling, and near miss) were applied to classification tasks …

Persistent link: https://www.econbiz.de/10015435682

A machine learning and explainable artificial intelligence triage-prediction system for COVID-19

Khanna, Varada Vivek; Chadaga, Krishnaraj; Sampathila, … - 2023

multiple pipelines entailing combinations of five state-of-the-art data-balancing techniques (Synthetic Minority Oversampling …

Persistent link: https://www.econbiz.de/10014497362

Machine learning and data balancing methods for bankruptcy prediction

Liashenko, Olena; Kravets, Tetyana; Kostovetskyi, Yevhenii - In: Ekonomika : mokslo žurnalas 102 (2023) 2, pp. 28-46

Persistent link: https://www.econbiz.de/10014428868

A model combining Optuna and the light gradient-boosting machine algorithm for credit default forecasting

Lu, Xinyong; Li, Yuchong; Wei, Haoyan; Wang, Jiaxin; … - In: The journal of risk model validation 18 (2024) 3, pp. 1-25

Persistent link: https://www.econbiz.de/10015459625

A hybrid detection system for ddos attacks based on deep sparse autoencoder and light gradient boost machine

Batchu, Raj Kumar; Seetha, Hari - In: Journal of information & knowledge management : JIKM 22 (2023) 1, pp. 1-26

Persistent link: https://www.econbiz.de/10014385019