Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing

Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing

In recent years, the huge expansion of digital technologies has vastly increased the volume of data to be explored, such that reducing the dimensionality of data is an essential step in data exploration. The integrity of a dimensionality reduction technique relates to the goodness of maintaining the...

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Bibliographic Details
Main Authors: Laureta Hajderanj, Daqing Chen, Enrico Grisan, Sandra Dudley
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Dimensionality reduction
global structure
local structure
visualization
structure capturing
manifold learning
Online Access:https://ieeexplore.ieee.org/document/9261480/

Internet

https://ieeexplore.ieee.org/document/9261480/

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