Search alternatives:
learning algorithm » learning algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
develop based » developed based (Expand Search), develop masld (Expand Search), development based (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
develop based » developed based (Expand Search), develop masld (Expand Search), development based (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
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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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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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Ranking of ML algorithms.
Published 2025“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”
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Algorithmic experimental parameter design.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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The overview of the ML algorithms’ flowchart.
Published 2025“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”
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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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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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Spatial spectrum estimation for three algorithms.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”