Search Results - subject:"Hyperparameter tuning"

Using sequential statistical tests for efficient hyperparameter tuning

Buczak, Philip; Groll, Andreas; Pauly, Markus; Rehof, Jakob - In: AStA Advances in Statistical Analysis 108 (2024) 2, pp. 441-460

Hyperparameter tuning is one of the most time-consuming parts in machine learning. Despite the existence of modern … underscore the potential for integrating sequential tests into hyperparameter tuning. …

Persistent link: https://www.econbiz.de/10015361330

Predicting machine failures using machine learning and deep learning algorithms

Yadav, Devendra K.; Kaushik, Aditya; Yadav, Nidhi - In: Sustainable manufacturing and service economics 3 (2024), pp. 1-11

Industry 4.0 emphasizes real-time data analysis for understanding and optimizing physical processes. This study leverages a Predictive Maintenance Dataset from the UCI repository to predict machine failures and categorize them. This study covers two objectives namely, to compare the performance...

Persistent link: https://www.econbiz.de/10015332702

The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index

Thi Thu Giang Nguyen; Ślepaczuk, Robert - 2022

Persistent link: https://www.econbiz.de/10013474013

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

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

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

Purpose The world is shifting towards the fourth industrial revolution (Industry 4.0), symbolising the move to digital, fully automated habitats and cyber-physical systems. Industry 4.0 consists of innovative ideas and techniques in almost all sectors, including Smart health care, which...

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

Towards a scalable anomaly detection with pseudo-optimal hyperparameters

Vanhoeyveld, Jellis; Martens, David - 2018

Persistent link: https://www.econbiz.de/10012243143