Self-Regulation of Neighborhood Parameter for Locally Linear Embedding
2013 ◽
Vol 677
◽
pp. 436-441
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Keyword(s):
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, a new method called Self-Regulated LLE is proposed. It achieves to solve the problem of deciding appropriate neighborhood parameter for LLE by finding the local patch which is close to be a linear one. The experiment results show that LLE with self-regulation performs better in most cases than LLE based on different evaluation criteria and spends less time on several data sets.
2005 ◽
pp. 101-109
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2010 ◽
Vol 23
(5-6)
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pp. 327-338
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Keyword(s):
2014 ◽
Vol 11
(7)
◽
pp. 2109-2116
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Keyword(s):
2005 ◽
Vol 31
(6)
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pp. 689-697
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2014 ◽
Vol 11
(10)
◽
pp. 1712-1716
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2014 ◽
Vol 1014
◽
pp. 375-378
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