<italic>l</italic><sub>2,<italic>p</italic></sub>-Norm Based Discriminant Subspace Clustering Algorithm

<italic>l</italic><sub>2,<italic>p</italic></sub>-Norm Based Discriminant Subspace Clustering Algorithm

Discriminative subspace clustering (DSC) combines Linear Discriminant Analysis (LDA) with clustering algorithm, such as K-means (KM), to form a single framework to perform dimension reduction and clustering simultaneously. It has been verified to be effective for high-dimensional data. However, most...

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Bibliographic Details
Main Authors: Xiaobin Zhi, Longtao Bi, Jiulun Fan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Subspace clustering
linear discriminant analysis
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iterative reweighted least squares
robustness
Online Access:https://ieeexplore.ieee.org/document/9072148/

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https://ieeexplore.ieee.org/document/9072148/

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