Results 31 to 40 of about 387,320 (324)
A new unsupervised feature selection method for text clustering based on genetic algorithms [PDF]
, 2011 Nowadays a vast amount of textual information is collected and stored in various databases around the world, including the Internet as the largest database of all.
Saraee, MH, Shamsinejadbabki, P
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Unsupervised Cluster-Wise Hyperspectral Band Selection for Classification
Remote Sensing, 2022 A hyperspectral image provides fine details about the scene under analysis, due to its multiple bands. However, the resulting high dimensionality in the feature space may render a classification task unreliable, mainly due to overfitting and the Hughes ...
Mateus Habermann +2 more
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Semi-supervised feature selection via multiobjective optimization [PDF]
, 2006 In previous work, we have shown that both unsupervised feature selection and the semi-supervised clustering problem can be usefully formulated as multiobjective optimization problems.
Joshua Knowles, Julia Handl
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IEEE Access, 2020 The open-circuit faults of power semiconductor devices in multilevel converters are generally diagnosed by analyzing circuit signals. For converters with five or more levels, the difficulty of fault detection increases with increasing topological ...
Shu Ye +4 more
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Structure Preserving Unsupervised Feature Selection Based on Autoencoder and Manifold Regularization [PDF]
Jisuanji kexue, 2021 There are a lot of redundant and irrelevant features in high-dimensional data,which seriously affect the efficiency and quality of data mining and the generalization performance of machine learning.Therefore,feature selection has become an important ...
YANG Lei, JIANG Ai-lian, QIANG Yan
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Heterogeneous feature space based task selection machine for unsupervised transfer learning [PDF]
, 2015 © 2015 IEEE. Transfer learning techniques try to transfer knowledge from previous tasks to a new target task with either fewer training data or less training than traditional machine learning techniques.
Lu, J, Xiong, L, Xue, S, Zhang, G
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IEEE Access, 2018 Feature selection plays an important role in preprocessing in pattern recognition and data mining, especially in large scale image, digital text, and biological data.
Yintong Wang
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Automatic Dataset Labelling and Feature Selection for Intrusion Detection Systems [PDF]
, 2014 The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Correctly labelled datasets are commonly required.
Aparicio-Navarro, Francisco J. +2 more
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SHAP-Based Feature Selection for Enhanced Unsupervised Labeling
IEEE AccessManual dataset labeling is expensive, time-consuming, and susceptible to noise and inaccuracies, often necessitating significant financial investments with risks of inconsistencies from human annotations.
Mary Anne Walauskis +1 more
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Unsupervised Feature Selection With Ordinal Preserving Self-Representation
IEEE Access, 2018 Unsupervised feature selection is designed to select an optimal feature subset without any label information from high-dimensional data, which is implemented by eliminating the irrelevant and redundant features and has been attracted widespread attention
Jiangyan Dai +6 more
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