Results 21 to 30 of about 185,151 (349)
Ensemble - an E-Learning Framework [PDF]
J. Univers. Comput. Sci., 2013 JUCS - Journal of Universal Computer Science Volume Nr.
Queirós, Ricardo, Leal, José Paulo
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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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Infinite Ensemble Learning with Support Vector Machines [PDF]
, 2005 Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of base learners. However, existing algorithms are limited to combining only a finite number of base learners, and the generated ensemble is ...
Lin, Hsuan-Tien
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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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Fractal-Based Ensemble Classification System for Hyperspectral Images [PDF]
, 2023 According to the literature, the utilization of spatial features can significantly enhance the accuracy of hyperspectral image (HSI) classification. Fractal features are powerful measures of texture, representing the local complexity of an image.
Beirami, Behnam Asghari +2 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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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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Learning with Pseudo-Ensembles
CoRR, 2014 To appear in Advances in Neural Information Processing Systems 27 (NIPS 2014), Advances in Neural Information Processing Systems 27, Dec ...
Philip Bachman +2 more
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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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