Results 11 to 20 of about 3,745,728 (280)
An incremental approach to MSE-based feature selection [PDF]
, 2007 Feature selection plays an important role in classification systems. Using classifier error rate as the evaluation function, feature selection is integrated with incremental training.
Guan, SU, Bao, C, Qi, Y
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Unsupervised Feature Selection Based on Self-configuration Approaches using Multidimensional Scaling
Jambura Journal of Mathematics, 2023 Some researchers often collect features so the principal information does not lose. However, many features sometimes cause problems. The truth of analysis results will decrease because of the irrelevant or repetitive features.
Ridho Ananda +4 more
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Autoencoder Inspired Unsupervised Feature Selection [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 High-dimensional data in many areas such as computer vision and machine learning tasks brings in computational and analytical difficulty. Feature selection which selects a subset from observed features is a widely used approach for improving performance and effectiveness of machine learning models with high-dimensional data. In this paper, we propose a
Kai Han 0002 +4 more
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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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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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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
Xiaoying Xing +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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The role of classifiers in feature selection: Number vs nature [PDF]
, 2008 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Wrapper feature selection approaches are widely used to select a small subset of relevant features from a dataset.
Chrysostomou, Kyriacos Andrews
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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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Feature weighting as a tool for unsupervised feature selection [PDF]
Information Processing Letters, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Deepak Panday +2 more
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