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TensorClus: A python library for tensor (Co)-clustering

delete2022-01-01
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Rafika Boutalbi *
L
Lazhar Labiod
M
Mohamed Nadif
DOI:10.1016/j.neucom.2021.09.036delete
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摘要

摘要

En 中文
Tensor data analysis is the evolutionary step of data analysis to more than two dimensions. Dealing with tensor data is often based on tensor decomposition methods. The present paper focuses on unsupervised learning and provides a python package referred to as TensorClus including novel co-clustering algorithms of three-way data. All proposed algorithms are based on the latent block models and suitable to different types of data, sparse or not. They are successfully evaluated on challenges in text mining, recommender systems, and hyperspectral image clustering. TensorClus is an open-source Python package that allows easy interaction with other python packages such as NumPy and TensorFlow; it also offers an interface with some tensor decomposition packages namely Tensorly and TensorD on the one hand, and on the other, the co-clustering package Co clust. Finally, it provides CPU and GPU compatibility. The TensorClus library is available at https://pypi.org/project/TensorClus/. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Tensors
(Co)-clustering
Multiple graphs
Tensor decomposition
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期刊

Neurocomputing 封面图
Neurocomputing
IF:
6.5
论文数:
2.5W
被引数:
6.5W

机构

U
University of Stuttgart
学者数:
1.1W
论文数: 9.4K
被引数: 1.3W
C
centre national de la recherche scientifique (cnrs)
学者数:
24.5W
论文数: 18.2W
被引数: 279
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