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data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
data processing » image processing (Expand Search)
data clustering » deep clustering (Expand Search), spatial clustering (Expand Search), dbscan clustering (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
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The relevant code in the manuscript can be found in the supporting information data file.
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Comparison of the EODA algorithm with existing algorithms in terms of recall.
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Comparison of the EODA algorithm with existing algorithms in terms of precision.
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Comparison of the EODA algorithm with existing algorithms in terms of F1-Score.
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K-means++ clustering algorithm.
Published 2025“…Subsequently, the feature factors corresponding to the model with the highest accuracy were selected as the optimal feature subsets and used in the model construction as input data. Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”
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Model-Based Clustering of Categorical Data Based on the Hamming Distance
Published 2024“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”
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