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nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
we decrease » _ decrease (Expand Search), mean decrease (Expand Search), teer decrease (Expand Search)
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50 nn » 50 ns (Expand Search), 50 ng (Expand Search), 50 n (Expand Search)
means decrease » mean decrease (Expand Search), deaths decreased (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
we decrease » _ decrease (Expand Search), mean decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
k means » _ means (Expand Search)
50 nn » 50 ns (Expand Search), 50 ng (Expand Search), 50 n (Expand Search)
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K-means++ clustering algorithm.
Published 2025“…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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Predicting pattern diversity decreases as a function of and .
Published 2025“…<p>For 50 Erdős-Rényi graphs with 30 nodes and 70 edges, we split the results into two columns according to the two initial degenerate unstable eigenmodes + : on the left, (if ), and on the right, (if ). …”
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