Semi-Supervised Dimensionality Reduction by Linear Compression and Stretching

Semi-Supervised Dimensionality Reduction by Linear Compression and Stretching

Dimensionality reduction is a fundamental and important research topic in the field of machine learning. This paper focuses on a dimensionality reduction technique that exploits semi-supervising information in the form of pairwise constraints; specifically, these constraints specify whether two inst...

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Bibliographic Details
Main Authors: Zhiguo Long, Hua Meng, Michael Sioutis
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Dimensionality reduction
pairwise constraints
PCA
FLD
Online Access:https://ieeexplore.ieee.org/document/8981950/

Internet

https://ieeexplore.ieee.org/document/8981950/

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