Research on PCA-Kmeans++ clustering algorithm considering Spatiotemporal dimension

Aiming at the problem that traditional clustering algorithms cannot adapt to spatiotemporal data mining, this paper proposes a new clustering algorithm PCA-Kmeans++. First, in order to reduce the interference of data dimension, an improved PCA (principal component analysis) dimensionality reduction...

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Bibliographic Details

Published in:	2023 2nd International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME) pp. 195 - 201
Main Authors:	Huang, Jiale, Dai, Jingtong, Li, Yanjin
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2023
Subjects:	AFC Data Classification algorithms Clustering algorithms Data mining Dimensionality reduction Interference K-means PCA Spatiotemporal clustering algorithm Spatiotemporal phenomena Visualization
Online Access:	Get full text
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