RMFRASL: Robust Matrix Factorization with Robust Adaptive Structure Learning for Feature Selection

RMFRASL: Robust Matrix Factorization with Robust Adaptive Structure Learning for Feature Selection

In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the performance of classification and clustering ta...

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Bibliographic Details
Main Authors: Shumin Lai, Longjun Huang, Ping Li, Zhenzhen Luo, Jianzhong Wang, Yugen Yi
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Algorithms
Subjects:
feature selection
matrix factorization
adaptive structure learning
structure regularization
Online Access:https://www.mdpi.com/1999-4893/16/1/14

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