A Prediction for the Cluster Centers in Unlabeled Data

Yu Hsuan Lee, Wen June Wang, Sheng Kai Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This article proposes an algorithm to predict the cluster centers and their locations in unlabeled data in which we do not know how many clusters in advance. The proposed method is a recursive algorithm and has good performance to deal with the clustering problem in data with or without noise.

Original languageEnglish
Title of host publicationICSSE 2022 - 2022 International Conference on System Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-138
Number of pages6
ISBN (Electronic)9781665488525
DOIs
StatePublished - 2022
Event2022 International Conference on System Science and Engineering, ICSSE 2022 - Virtual, Online, Taiwan
Duration: 26 May 202229 May 2022

Publication series

NameICSSE 2022 - 2022 International Conference on System Science and Engineering

Conference

Conference2022 International Conference on System Science and Engineering, ICSSE 2022
Country/TerritoryTaiwan
CityVirtual, Online
Period26/05/2229/05/22

Keywords

  • classify
  • unlabeled data
  • unsupervised

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