Fuzzy Granule Manifold Alignment Preserving Local Topology

Fuzzy Granule Manifold Alignment Preserving Local Topology

Granular computing has the advantage of discovering complex data knowledge, and manifold alignment has proven of great value in a lot of areas of machine learning. We propose a novel algorithm of fuzzy granule manifold alignment (FGMA), where we define some new operations, measurements, and local to...

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Bibliographic Details
Main Authors: Wei Li, Jianwu Xue, Yumin Chen, Xuebai Zhang, Chao Tang, Qiang Zhang, Yifang Gao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Granular computing
fuzzy sets
manifold learning
alignment
local topology
Online Access:https://ieeexplore.ieee.org/document/9207930/

Internet

https://ieeexplore.ieee.org/document/9207930/

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