Search Results - subject:"hyperparameter"

Machine learning prediction of loss given default in government-sponsored enterprise residential mortgages

Liu, Zilong; Liang, Hongyan - In: The journal of risk model validation 18 (2024) 2, pp. 1-23

Persistent link: https://www.econbiz.de/10015459249

Use of static surrogates in hyperparameter optimization

Lakhmiri, Dounia; Le Digabel, Sébastien - 2021

Persistent link: https://www.econbiz.de/10012588176

A multilayer feedforward perceptron model in neural networks for predicting stock market short-term trends

Namdari, Alireza; Durrani, Tariq S. - In: Operations research forum 2 (2021) 3, pp. 1-30

Persistent link: https://www.econbiz.de/10012589934

Predicting stock splits using ensemble machine learning and SMOTE oversampling

Li, Ang; Liu, Mark H.; Sheather, Simon J. - In: Pacific-Basin finance journal 78 (2023), pp. 1-24

Persistent link: https://www.econbiz.de/10014463767

Application of a stochastic schemata exploiter for multi-objective hyper-parameter optimization of machine learning

Makino, Hiroya; Kita, Eisuke - In: The review of socionetwork strategies 17 (2023) 2, pp. 179-213

Persistent link: https://www.econbiz.de/10014425714

Machine learning-based construction site dynamic risk models

Gondia, Ahmed; Moussa, Ahmed; Ezzeldin, Mohamed; … - In: Technological forecasting & social change : an … 189 (2023), pp. 1-17

Persistent link: https://www.econbiz.de/10014266221

Prescriptive selection of machine learning hyperparameters with applications in power markets : retailer's optimal trading

Corredera, Alberto; Ruiz, Carlos - In: European journal of operational research : EJOR 306 (2023) 1, pp. 370-388

Persistent link: https://www.econbiz.de/10014278011

Use of static surrogates in hyperparameter optimization

Lakhmiri, Dounia; Le Digabel, Sébastien - In: Operations research forum 3 (2022) 1, pp. 1-18

Persistent link: https://www.econbiz.de/10012819316

Forecasting chlorophyll-a concentration using empirical wavelet transform and support vector regression

Yu, Jin-Won; Kim, Ju-Song; Jong, Yun-Chol; Li, Xia; … - In: Journal of forecasting 41 (2022) 8, pp. 1691-1700

Persistent link: https://www.econbiz.de/10013465740

Industry 4.0 oriented predictive analytics of cardiovascular diseases using machine learning, hyperparameter tuning and ensemble techniques

Ahamed, Jameel; Mir, Roohie Naaz; Chishti, Mohammad Ahsan - In: Industrial Robot: the international journal of robotics … 49 (2022) 3, pp. 544-554

, hyperparameter optimisation techniques are used to develop efficient disease prediction models. Furthermore, the ensemble technique ….0. Prediction models are developed on algorithms’ default values, hyperparameter optimisations and ensemble techniques. …

Persistent link: https://www.econbiz.de/10014835976