Title page for etd-0630113-100203


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URN etd-0630113-100203
Author Chien-Hung Tung
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2012
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title An Elastic Net Algorithm for Clustering
Date of Defense 2013-07-03
Page Count 52
Keyword
  • data clustering
  • KGA
  • k-means
  • GKA
  • elastic net
  • non-linearly separable
  • Abstract  This paper presents an effective elastic net-based clustering algorithm for complex and non-linearly separable data. The basic idea of the proposed algorithm is simple and can be summarized into two steps: (1) assign patterns to groups based on the attraction and tension between the elastic nodes in a ring and the neighbors of the patterns and (2) merge the groups based on the distances between the elastic nodes.
     
     To evaluate the performance of the proposed method, we compare it with several state-of-the-art clustering methods in solving the data clus tering problem. The simulation results show that the proposed algorithm outperforms the other clustering algorithms compared in terms of the accuracy rate. The results also show that the proposed algorithm works well for complex datasets, especially non-linearly separable data.
    Advisory Committee
  • Chu-Sing Yang - chair
  • Tzung-Pei Hong - co-chair
  • Chun-Wei Tsai - co-chair
  • Ming-Chao Chiang - advisor
  • Files
  • etd-0630113-100203.pdf
  • Indicate in-campus at 99 year and off-campus access at 99 year.
    Date of Submission 2013-07-30

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