AutoClustering: A feed-forward neural network based clustering algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Since a clustering process can be regarded as a map of data to cluster labels, it should be natural to employ a deep learning technique, especially a feed-forward neural network, to realize the clustering method. In this study, we discussed a novel clustering method realized only by a feed-forward neural network. Unlike self-organizing maps and growing neural gas networks, the proposed method is compatible with deep learning neural networks. The proposed method has three parts: A map of records to clusters (encoder), a map of clusters to their exemplars (decoder), and a loss function to measure positional closeness between the records and the exemplars. In order to accelerate clustering performance, we proposed an improved activation function at the encoder, which migrates a soft-max function to a max function continuously. Though most of the clustering methods require the number of clusters in advance, the proposed method naturally provides the number of clusters as the number of unique one-hot vectors obtained as a result. We also discussed the existence of local minima of the loss function and their relationship to clusters.

Original languageEnglish
Title of host publicationProceedings - 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018
EditorsJeffrey Yu, Zhenhui Li, Hanghang Tong, Feida Zhu
PublisherIEEE Computer Society
Pages659-666
Number of pages8
ISBN (Electronic)9781538692882
DOIs
Publication statusPublished - 2019 Feb 7
Event18th IEEE International Conference on Data Mining Workshops, ICDMW 2018 - Singapore, Singapore
Duration: 2018 Nov 172018 Nov 20

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
Volume2018-November
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Conference

Conference18th IEEE International Conference on Data Mining Workshops, ICDMW 2018
CountrySingapore
CitySingapore
Period18/11/1718/11/20

Keywords

  • Autoencoder
  • Clustering
  • Feed forward neural network

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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  • Cite this

    Kimura, M. (2019). AutoClustering: A feed-forward neural network based clustering algorithm. In J. Yu, Z. Li, H. Tong, & F. Zhu (Eds.), Proceedings - 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018 (pp. 659-666). [8637379] (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2018-November). IEEE Computer Society. https://doi.org/10.1109/ICDMW.2018.00102