Sparsity Fuzzy C-Means Clustering with Principal Component Analysis Embedding

The clustering method has been widely used in data mining, pattern recognition, and image identification. Fuzzy c-means (FCM) is a soft clustering method that introduces the concept of membership. In this method, the fuzzy membership matrix is obtained by calculating the distance between data points...

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Veröffentlicht in:	IEEE transactions on fuzzy systems Jg. 31; H. 7; S. 1 - 13
Hauptverfasser:	Chen, Jingwei, Zhu, Jianyong, Jiang, Hongyun, Yang, Hui, Nie, Feiping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Clustering Clustering algorithms Clustering methods Data analysis Data mining Data points Dimensionality reduction Embedding Feature extraction Fuzzy c-means (FCM) Iterative methods Noise sensitivity Optimization outliers Outliers (statistics) Pattern recognition Principal component analysis principal component analysis (PCA) Principal components analysis Robustness Sparsity
ISSN:	1063-6706, 1941-0034
Online-Zugang:	Volltext
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