Unsupervised Feature Selection Based on Low-Rank Regularized Self-Representation
نویسندگان
چکیده
منابع مشابه
Self-representation based dual-graph regularized feature selection clustering
Feature selection algorithms eliminate irrelevant and redundant features, even the noise, while preserving the most representative features. They can reduce the dimension of the dataset, extract essential features in high dimensional data and improve learning quality. Existing feature selection algorithms are all carried out in data space. However, the information of feature space cannot be ful...
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ژورنال
عنوان ژورنال: OALib
سال: 2020
ISSN: 2333-9721,2333-9705
DOI: 10.4236/oalib.1106274