Results 11 to 20 of about 31,707 (257)
Entropy-Based Bagging for Fault Prediction of Transformers Using Oil-Dissolved Gas Data
Energies, 2011 The development of the smart grid has resulted in new requirements for fault prediction of power transformers. This paper presents an entropy-based Bagging (E-Bagging) method for prediction of characteristic parameters related to power transformers ...
Weigen Chen +4 more
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Performance Analysis of Classification Algorithms on Birth Dataset
IEEE Access, 2020 Generating intuitions from data using data mining and machine learning algorithms to predict outcomes is useful area of computing. The application area of data mining techniques and machine learning is wide ranging including industries, healthcare ...
Syed Ali Abbas +6 more
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Bagging ensemble selection [PDF]
, 2011 Ensemble selection has recently appeared as a popular ensemble learning method, not only because its implementation is fairly straightforward, but also due to its excellent predictive performance on practical problems.
Quan Sun +3 more
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Construction of Machine-Labeled Data for Improving Named Entity Recognition by Transfer Learning
IEEE Access, 2020 Deep neural networks (DNNs) require a large amount of manually labeled training data to make significant achievements. However, manual labeling is laborious and costly.
Juae Kim, Youngjoong Ko, Jungyun Seo
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Effect of Different Fruit Bags on Fruit Quality of 'Cuiguan' Pear
Guangdong nongye kexue, 2023 【Objective】By comparing the quality of 'Cuiguan' pear fruits under five different bag treatments, from which the bag that can improve the appearance quality of fruits and has less impact on the internal quality of the fruits was selected, with an aim to ...
Jinghan FENG +5 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
Quan Sun +3 more
core +1 more source
RolexBoost: A Rotation-Based Boosting Algorithm With Adaptive Loss Functions
IEEE Access, 2020 We propose a new ensemble algorithm, called RolexBoost (Rotation-Flexible AdaBoost) that can not only secure diversity within an ensemble by rotating the feature axes in conjunction with performing the random subspace method for each bootstrap sample ...
Dong-Hyuk Yang +2 more
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Improving adaptive bagging methods for evolving data streams [PDF]
, 2009 We propose two new improvements for bagging methods on evolving data streams. Recently, two new variants of Bagging were proposed: ADWIN Bagging and Adaptive-Size Hoeffding Tree (ASHT) Bagging.
Pfahringer, Bernhard +7 more
core +1 more source
Sensors, 2022 The performance of a six-axis force/torque sensor (F/T sensor) severely decreased when working in an extreme environment due to its sensitivity to ambient temperature. This paper puts forward an ensemble temperature compensation method based on the whale
Xuhao Li +5 more
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Preharvest fruit bagging time regulates postharvest quality and shelf life of dragon fruit (Hylocereus spp.) [PDF]
International Journal of Minor Fruits, Medicinal and Aromatic Plants, 2021 Appropriate bagging time is imperative for effective use of fruit bagging technology in safe fruit production. A study was conducted at the Germplasm Centre of Bangladesh Agricultural University (BAU-GPC), Mymensingh during May 2018 to September 2019 ...
Md. Mokter Hossain1
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