Results 11 to 20 of about 61,068 (254)
Case Studies in Chemical and Environmental Engineering, 2023 This research used machine-learning-based forecasting models to estimate a Supervisory control and data acquisition system's wind speed and electricity production.
Seyed Matin Malakouti
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Distributional Gradient Boosting Machines
CoRR, 2022 Distributional Regression, LightGBM, Normalizing Flow, Probabilistic Forecasting ...
Alexander März, Thomas Kneib
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A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects
IEEE Access, 2022 Ensemble learning techniques have achieved state-of-the-art performance in diverse machine learning applications by combining the predictions from two or more base models.
Ibomoiye Domor Mienye, Yanxia Sun
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Machine learning techniques for classifying dangerous asteroids
MethodsX, 2023 There is an infinite number of objects in outer space, and these objects and asteroids might be harmful. Hence, it is wise to know what is surrounding us and what can harm us amongst those.Therefore, in this article, with the hyperparameters tuning of ...
Seyed Matin Malakouti +2 more
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Gradient Boosting Machine with Partially Randomized Decision Trees [PDF]
2021 28th Conference of Open Innovations Association (FRUCT), 2021 The gradient boosting machine is a powerful ensemble-based machine learning method for solving regression problems. However, one of the difficulties of its using is a possible discontinuity of the regression function, which arises when regions of training data are not densely covered by training points.
Andrei V. Konstantinov +2 more
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Frontiers in Public Health, 2022 BackgroundIn this paper, we examine whether machine learning and deep learning can be used to predict difficult airway intubation in patients undergoing thyroid surgery.MethodsWe used 10 machine learning and deep learning algorithms to establish a ...
Cheng-Mao Zhou +7 more
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Soft Gradient Boosting Machine
CoRR, 2020 Gradient Boosting Machine has proven to be one successful function approximator and has been widely used in a variety of areas. However, since the training procedure of each base learner has to take the sequential order, it is infeasible to parallelize the training process among base learners for speed-up.
Ji Feng +3 more
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Favorite Book Prediction System Using Machine Learning Algorithms
Journal of Applied Engineering and Technological Science, 2023 Recent years have seen the rapid deployment of Artificial Intelligence (AI) which allows systems to take intelligent decisions. AI breakthroughs could radically change modern libraries' operations.
Dersin Daimari +3 more
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Using machine learning to improve risk prediction in durable left ventricular assist devices.
PLoS ONE, 2021 Risk models have historically displayed only moderate predictive performance in estimating mortality risk in left ventricular assist device therapy. This study evaluated whether machine learning can improve risk prediction for left ventricular assist ...
Arman Kilic +4 more
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Accelerating Gradient Boosting Machine
CoRR, 2019 Gradient Boosting Machine (GBM) is an extremely powerful supervised learning algorithm that is widely used in practice. GBM routinely features as a leading algorithm in machine learning competitions such as Kaggle and the KDDCup. In this work, we propose Accelerated Gradient Boosting Machine (AGBM) by incorporating Nesterov's acceleration techniques ...
Lu, Haihao +3 more
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