Results 11 to 20 of about 387,320 (324)
Unsupervised Feature Selection with Latent Relationship Penalty Term
Axioms, 2023 With the exponential growth of high dimensional unlabeled data, unsupervised feature selection (UFS) has attracted considerable attention due to its excellent performance in machine learning.
Ziping Ma +3 more
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Improved SOCFS Algorithm Based on Triplet Ordinal Locality [PDF]
Jisuanji gongcheng, 2020 Features selection is commonly used in dimensionality reduction of machine learning,but existing unsupervised feature selection algorithms often ignore the influence of ordinal locality on feature selection while preserving the local structure of ...
WU Changming, ZHAO Xingtao, LIU Kexin
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Algorithms, 2023 Determining the optimal feature set is a challenging problem, especially in an unsupervised domain. To mitigate the same, this paper presents a new unsupervised feature selection method, termed as densest feature graph augmentation with disjoint feature ...
Deepesh Chugh +5 more
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Fairness-Aware Unsupervised Feature Selection [PDF]
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021 Feature selection is a prevalent data preprocessing paradigm for various learning tasks. Due to the expensive cost of acquiring supervision information, unsupervised feature selection sparks great interests recently. However, existing unsupervised feature selection algorithms do not have fairness considerations and suffer from a high risk of amplifying
Xing, Xiaoying +3 more
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Robust Low-rank Self-representation Feature Selection Algorithm [PDF]
Jisuanji gongcheng, 2017 Since unsupervised feature selection algorithms do not have label information and also ignore the low-rank characteristics of the data,this paper proposes a new low-rank feature selection algorithm based on self-representation method.In the loss function,
HU Rongyao,LIU Xingyi,CHENG Debo,HE Wei,LUO Yan
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Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security
Applied Sciences, 2021 Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns.
Michael Heigl +3 more
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Review of feature selection approaches based on grouping of features [PDF]
PeerJ, 2023 With the rapid development in technology, large amounts of high-dimensional data have been generated. This high dimensionality including redundancy and irrelevancy poses a great challenge in data analysis and decision making. Feature selection (FS) is an
Cihan Kuzudisli +4 more
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Joint Multi-View Unsupervised Feature Selection and Graph Learning [PDF]
IEEE Transactions on Emerging Topics in Computational Intelligence, 2022 Despite significant progress, previous multi-view unsupervised feature selection methods mostly suffer from two limitations. First, they generally utilize either cluster structure or similarity structure to guide the feature selection, which neglect the ...
Siwei Fang +3 more
semanticscholar +1 more source
Journal of Information Science Theory and Practice, 2021 Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with ...
Qusay Bsoul +3 more
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Unsupervised Dual Learning for Feature and Instance Selection
IEEE Access, 2020 Feature selection and instance selection are dual operations on a data matrix. Feature selection aims at selecting a subset of relevant and informative features from original feature space, while instance selection at identifying a subset of informative ...
Liang Du, Xin Ren, Peng Zhou, Zhiguo Hu
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