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Subspace clustering (SC) is a promising technology involving clusters that are identified based on their association with subspaces in high-dimensional spaces.
This paper presents a new sequential clustering algorithm based on sequential hard c-means clustering. The word sequential cluster extraction means that the ...
This paper presents kernel-based hard clustering methods with kernelization of the metric and automatic weighting of the variables.
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This paper presents a new sequential clustering algorithm based on sequential hard c-means clustering. The word sequential cluster extraction means that the ...
Bibliographic details on On Kernelized Sequential Hard Clustering.
This paper studies the optimality of kernel methods in high-dimensional data clustering. Recent works have studied the large sample.
On some hierarchical clustering algorithms using kernel functions ...
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A kernelized sequentialhard clustering is proposed by introducing the kernel method to sequential hard clustering to handle datasets which consists ...
This paper presents variable-wise kernel hard clustering algorithms in the feature space in which dissimilarity measures are obtained as sums of squared ...
Missing: Sequential | Show results with:Sequential
Oct 22, 2024 · This paper presents kernel-based hard clustering methods with kernelization of the metric and automatic weighting of the variables.
Missing: Sequential | Show results with:Sequential