LAUSR

Unsupervised Adaptive Embedding for Dimensionality Reduction.

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0 Published in 2021 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2021.3083695

Abstract: High-dimensional data are highly correlative and redundant, making it difficult to explore and analyze. Amount of unsupervised dimensionality reduction (DR) methods has been proposed, in which constructing a neighborhood graph is the primary step of… read more here.

Keywords: unsupervised adaptive; method; dimensionality reduction; adaptive embedding ... See more keywords