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Abstract Clustering is a widely applied method in data analysis. As a novel framework of clustering analysis, penalized clustering bases itself on the sparsity of solution, which contributes to its… Click to show full abstract
Abstract Clustering is a widely applied method in data analysis. As a novel framework of clustering analysis, penalized clustering bases itself on the sparsity of solution, which contributes to its ability of determining the best number of clusters automatically rather than specified in advance. Moreover, l1/2 regularization has been recognized extensively in recent studies. Compared with other lp (0
Keywords:
clustering half;
based penalized;
penalized clustering;
half thresholding;
thresholding algorithm
Journal Title: Neurocomputing
Year Published: 2020
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Journal Title: Neurocomputing
Year Published: 2020
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!