Adaptive initialization method based on spatial local information for \(k\)-means algorithm

DOI10.1155/2014/761468zbMath1407.62227OpenAlexW1997601773WikidataQ57971393 ScholiaQ57971393MaRDI QIDQ1719093

Jinhai Xiang, Honghong Liao, Jianghua Dai, Wei-ping Sun, Sheng Sheng Yu

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/761468

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Initializing \(k\)-means clustering by bootstrap and data depth

Uses Software

• k-means++

Cites Work

• Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm
• Clustering to minimize the maximum intercluster distance
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
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