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using algorithm » using algorithms (Expand Search), routing algorithm (Expand Search), fusion algorithm (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
trained using » obtained using (Expand Search), examined using (Expand Search), determined using (Expand Search)
using algorithm » using algorithms (Expand Search), routing algorithm (Expand Search), fusion algorithm (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
trained using » obtained using (Expand Search), examined using (Expand Search), determined using (Expand Search)
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The mAP for all algorithms and 80% of the data used for training.
Published 2024“…<p>The mAP for all algorithms and 80% of the data used for training.</p>…”
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The mAP for all algorithms and 50% of the data used for training.
Published 2024“…<p>The mAP for all algorithms and 50% of the data used for training.</p>…”
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The mAP for all algorithms and 60% of the data used for training.
Published 2024“…<p>The mAP for all algorithms and 60% of the data used for training.</p>…”
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Training algorithm flow.
Published 2024“…<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. …”
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List of the time used by each algorithm.
Published 2024“…In this manner high quality and common samples are randomly selected for training the classifier. Finally, to solve the issue of concept drift, EDAC designs and implements an ensemble classifier that uses a self-feedback strategy to determine the initial weight of the classifier by adjusting the weight of the sub-classifier according to the performance on the arrived data chunks. …”
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The schematic diagram of the hierarchical clustering algorithm.
Published 2025Subjects: “…original multidimensional data…”
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Characteristics of training algorithms.
Published 2025“…The issue of overfitting is significantly resolved, unlike in the case of the Backpropagation Neural Network (BPNN), which is used as a benchmark for comparison. Overall, the proposed algorithm significantly improves data training accuracy and generalization performance.…”
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Performance metrics (compared with DXA-based measurement) for different prediction algorithms using all predictors in training data.
Published 2025“…<p>Performance metrics (compared with DXA-based measurement) for different prediction algorithms using all predictors in training data.</p>…”
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The silhouette coefficient scores for different algorithms at various levels.
Published 2025Subjects: “…original multidimensional data…”
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