Results 31 to 40 of about 6,303,129 (314)
A Double Penalty Model for Ensemble Learning
Mathematics, 2022 Modern statistical learning techniques often include learning ensembles, for which the combination of multiple separate prediction procedures (ensemble components) can improve prediction accuracy.
Wenjia Wang, Yi-Hui Zhou
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Machine Learning: Science and Technology, 2023 Multi-label classification (MLC) of aerial images is a crucial task in remote sensing image analysis. Traditional image classification methods have limitations in image feature extraction, leading to an increasing use of deep learning models, such as ...
Ming-Hseng Tseng
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Ensemble Multifeatured Deep Learning Models and Applications: A Survey
IEEE Access, 2023 Ensemble multifeatured deep learning methodology has emerged as a powerful approach to overcome the limitations of single deep learning models in terms of generalization, robustness, and performance.
Satheesh Abimannan +5 more
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A new ensemble learning approach to detect malaria from microscopic red blood cell images
Sensors International, 2023 Malaria is a life-threatening parasitic disease spread by infected female Anopheles mosquitoes. After analyzing it, microscopists detect this disease from the sample of microscopic red blood cell images. A professional microscopist is required to conduct
Mosabbir Bhuiyan, Md Saiful Islam
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Bagging ensemble selection for regression [PDF]
, 2012 Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have
D.H. Wolpert +10 more
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Intrusion detection based on ensemble learning for big data classification
Cluster Computing, 2023 The escalating frequency and sophistication of cyber threats pose significant challenges to traditional intrusion detection methods. Signature-based misuse detection, hybrid detection, and anomaly detection, while effective in isolation, often struggle ...
Farah Jemili, Rahma Meddeb, O. Korbaa
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A survey on evolutionary ensemble learning algorithm
智能科学与技术学报, 2021 Evolutionary ensemble learning integrates advantages of ensemble learning and evolutionary algorithm and is widely used in machine learning, data mining, and pattern recognition.Firstly, the theoretical basis, formation, and taxonomy are introduced ...
Yi HU +4 more
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Surface Water Quality Classification via CMAES Ensemble Method
Jisuanji kexue yu tansuo, 2020 In order to improve the quality of people’s daily life, the government departments continue to strengthen water quality management. However, artificial classification method cannot meet the needs of real-time processing, additionally the classification ...
CHEN Xingguo, XU Xiuying, CHEN Kangyang, YANG Guang
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ELBA-IoT: An Ensemble Learning Model for Botnet Attack Detection in IoT Networks
J. Sens. Actuator Networks, 2022 Due to the prompt expansion and development of intelligent systems and autonomous, energy-aware sensing devices, the Internet of Things (IoT) has remarkably grown and obstructed nearly all applications in our daily life.
Q. A. Al-Haija, Mu'awya Al-Dala'ien
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Acting together: ensemble as a democratic process in art and life [PDF]
, 2009 Traditionally drama in schools has been seen either as a learning medium with a wide range of curricular uses or as a subject in its own right. This paper argues that the importance of drama in schools is in the processes of social and artistic ...
Bernstein B. +19 more
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