Results 21 to 30 of about 545,363 (263)
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 Learning for Free with Evolutionary Algorithms ? [PDF]
, 2007 Evolutionary Learning proceeds by evolving a population of classifiers, from which it generally returns (with some notable exceptions) the single best-of-run classifier as final result.
Gagné, Christian +3 more
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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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Analysis of ensemble learning using simple perceptrons based on online learning theory [PDF]
, 2004 Ensemble learning of $K$ nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics.
A. Engel +9 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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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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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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