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learning algorithm » learning algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
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a learning » _ learning (Expand Search), e learning (Expand Search), q learning (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
based method » based methods (Expand Search)
a learning » _ learning (Expand Search), e learning (Expand Search), q learning (Expand Search)
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Types of machine learning algorithms.
Published 2024“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.</p><p>Materials and methods</p><p>This study used the latest nationally representative cross-sectional Bangladesh demographic health survey (BDHS), 2017–18 data. …”
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Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms
Published 2025“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”
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Algorithmic experimental parameter design.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Spatial spectrum estimation for three algorithms.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Convergence curve of the DBO algorithm.
Published 2025“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”
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Decision tree algorithms.
Published 2025“…Ensemble learning in supervised machine learning is also a common technique for handling imbalanced data. …”
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