HDBSCAN for 3-rd order tensor - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

HDBSCAN for 3-rd order tensor

Résumé

Several methods for triclustering three-dimensional data require the cluster size or the number of clusters in each dimension to be specified. To address this issue, the Multi-Slice Clustering (MSC) for 3-order tensor finds signal slices that lie in a low dimensional subspace for a rank-one tensor dataset in order to find a cluster based on the threshold similarity. We propose an extension algorithm called MSC-DBSCAN to extract the different clusters of slices that lie in the different subspaces from the data if the dataset is a sum of r rank-one tensor (r > 1). Our algorithm uses the same input as the MSC algorithm and can find the same solution for rank-one tensor data as MSC.
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hal-04713530 , version 1 (29-09-2024)

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Dina Faneva Andriantsiory, Joseph Ben Geloun, Mustapha Lebbah. HDBSCAN for 3-rd order tensor. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2024, Bruges, France. ⟨10.48550/arXiv.2303.07768⟩. ⟨hal-04713530⟩
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