Results 31 to 40 of about 197,316 (278)
Machine Learning-Based Forecasting of Bitcoin Price Movements
Proceedings of the International Conference on Applied Innovations in ITIn the volatile realm of cryptocurrency markets, this research explores the intricate dance of Bitcoin price dynamics through the lens of machine learning. Employing a multifaceted approach, we harness the power of Long Short-Term Memory (LSTM) networks,
Darko Angelovski +4 more
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Comparing ensemble learning algorithms and severity of illness scoring systems in cardiac intensive care units: a retrospective study [PDF]
Einstein (São Paulo)Objective: Logistic Regression has been used traditionally for the development of most predictor tools of intensive care unit mortality. The purpose of this study is to combine shared risk factors between patients undergoing cardiac surgery and intensive
Beatriz Nistal-Nuño
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International Journal of Machine Learning and CyberneticsAbstract This paper presents a computationally efficient variant of Gradient Boosting (GB) for multi-class classification and multi-output regression tasks. Standard GB uses a 1-vs-all strategy for classification tasks with more than two classes. This strategy entails that one tree per class and iteration has to be trained.
Seyedsaman Emami +1 more
openaire +3 more sources
Learning Nonlinear Functions Using Regularized Greedy Forest
, 2013 We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
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QUIC Network Traffic Classification Using Ensemble Machine Learning Techniques
Applied Sciences, 2023 The Quick UDP Internet Connections (QUIC) protocol provides advantages over traditional TCP, but its encryption functionality reduces the visibility for operators into network traffic.
Sultan Almuhammadi +2 more
doaj +1 more source
BuildingsThe standard approach for testing ordinary concrete compressive strength (CS) is to cast samples and test them after different curing times. However, testing adds cost and time to projects, and, therefore, construction sites experience delays.
Fei Zhu +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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Intelligent Systems with ApplicationsTree-based ensemble methods, such as Extreme Gradient Boosting (XGBoost) and Gradient Boosting models (GBM), are widely used for supervised learning due to their strong predictive capabilities.
Sherif Eneye Shuaib +2 more
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Atmosphere, 2023 Machine learning algorithms are applied to predict intense wind shear from the Doppler LiDAR data located at the Hong Kong International Airport. Forecasting intense wind shear in the vicinity of airport runways is vital in order to make intelligent ...
Afaq Khattak +3 more
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