Title page for etd-0628114-161349


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URN etd-0628114-161349
Author Tsung-hsien Lin
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2013
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title An Elastic Net Algorithm for Automatic Clustering
Date of Defense 2014-06-26
Page Count 52
Keyword
  • automatic clustering
  • number of clusters
  • clustering
  • elastic net clustering algorithm
  • non-linearly separable data
  • Abstract Clustering has always been playing a vital role in many different disciplines because it is an
    important tool for analyzing a set of unknown input patterns. However, some important issues
    related to clustering, such as automatically determining the number of clusters and partitioning
    non-linearly separable data, are never fully solved even though many researchers work on this
    subject for a long time. As such, a novel method based on the so-called elastic net clustering al-
    gorithm is presented in this thesis to deal with exactly the two issues: partitioning non-linearly
    separable data and automatically determining the number of clusters. To evaluate the perfor-
    mance of the proposed algorithm, we compare it with several state-of-the-art methods using
    several well-known datasets. The experimental results show that not only can the proposed
    algorithm find the appropriate number of clusters, it can also provide a higher accuracy rate
    than all the other methods compared in this study for most datasets.
    Advisory Committee
  • Chu-sing Yang - chair
  • Tzung-Pei Hong - co-chair
  • Chun-Wei Tsai - co-chair
  • Ming-chao Chiang - advisor
  • Files
  • etd-0628114-161349.pdf
  • Indicate in-campus at 99 year and off-campus access at 99 year.
    Date of Submission 2014-08-20

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