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models algorithm » modeling algorithm (Expand Search), novel algorithm (Expand Search), modbo algorithm (Expand Search)
develop based » developed based (Expand Search), develop masld (Expand Search), development based (Expand Search)
rf algorithm » _ algorithm (Expand Search), ii algorithm (Expand Search), art algorithms (Expand Search)
element rf » element ore (Expand Search), element ree (Expand Search), element _ (Expand Search)
models algorithm » modeling algorithm (Expand Search), novel algorithm (Expand Search), modbo algorithm (Expand Search)
develop based » developed based (Expand Search), develop masld (Expand Search), development based (Expand Search)
rf algorithm » _ algorithm (Expand Search), ii algorithm (Expand Search), art algorithms (Expand Search)
element rf » element ore (Expand Search), element ree (Expand Search), element _ (Expand Search)
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Evaluation of model aggregation algorithms.
Published 2024“…To address these challenges, this paper proposes a federated learning-based intrusion detection algorithm (NIDS-FGPA) that utilizes gradient similarity model aggregation. …”
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Ranking of ML algorithms.
Published 2025“…The AB model, on the other hand, has the highest error values in the test data set, but still provides an acceptable prediction accuracy. …”
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The overview of the ML algorithms’ flowchart.
Published 2025“…The AB model, on the other hand, has the highest error values in the test data set, but still provides an acceptable prediction accuracy. …”
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Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx
Published 2025“…Background and aims<p>Sessile serrated lesions (SSLs) are morphologically subtle and often misclassified as hyperplastic polyps (HPs), increasing colorectal cancer risks. We developed a machine learning (ML) model to improve endoscopic SSL diagnosis.…”
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Types of machine learning algorithms.
Published 2024“…<div><p>Background and objectives</p><p>Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. 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.…”
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Comparison of homomorphic encryption algorithms.
Published 2024“…To address these challenges, this paper proposes a federated learning-based intrusion detection algorithm (NIDS-FGPA) that utilizes gradient similarity model aggregation. …”
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