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dc.contributor.authorTong, Liu-
dc.contributor.authorRongyao, Hu-
dc.contributor.authorYongxin, Zhu-
dc.date.accessioned2023-03-30T07:08:13Z-
dc.date.available2023-03-30T07:08:13Z-
dc.date.issued2023-
dc.identifier.urihttps://link.springer.com/article/10.1007/s11042-022-13903-y-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7338-
dc.descriptionCC BYvi
dc.description.abstractSample correlations and feature relations are two pieces of information that are needed to be considered in the unsupervised feature selection, as labels are missing to guide model construction. Thus, we design a novel unsupervised feature selection scheme, in this paper, via considering the completed sample correlations and feature dependencies in a unified framework. Specifically, self-representation dependencies and graph construction are conducted to preserve and select the important neighbors for each sample in a comprehensive way.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectfeature selection schemevi
dc.subjectunified frameworkvi
dc.titleCompleted sample correlations and feature dependency-based unsupervised feature selectionvi
dc.typeBookvi
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