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Wu et al., 2016 - Google Patents

Group sparse feature selection on local learning based clustering

Wu et al., 2016

Document ID
1802244033478900076
Author
Wu Y
Wang C
Bu J
Chen C
Publication year
Publication venue
Neurocomputing

External Links

Snippet

Feature selection plays an important role in many machine learning applications. By extracting meaningful features and eliminating both redundancies and noises, it effectively improves the accuracy and efficiency of the learning algorithm. In this paper, an …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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