Nearest Neighbor Median Shift Clustering for Binary Data
February 11, 2019 ยท Entered Twilight ยท ๐ International Conference on Artificial Neural Networks
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Repo contents: .gitignore, LICENSE, README.md, _config.yml, build.sbt, core, distributed, local, project
Authors
Gaรซl Beck, Tarn Duong, Mustapha Lebbah, Hanane Azzag
arXiv ID
1902.04181
Category
cs.LG: Machine Learning
Cross-listed
cs.AI,
stat.ML
Citations
1
Venue
International Conference on Artificial Neural Networks
Repository
https://github.com/Clustering4Ever/Clustering4Ever
โญ 130
Last Checked
4 months ago
Abstract
We describe in this paper the theory and practice behind a new modal clustering method for binary data. Our approach (BinNNMS) is based on the nearest neighbor median shift. The median shift is an extension of the well-known mean shift, which was designed for continuous data, to handle binary data. We demonstrate that BinNNMS can discover accurately the location of clusters in binary data with theoretical and experimental analyses.
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