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A Distance Adaptive Embedding Method in Dimension Reduction

  • Yanting Niu
  • Yueming Lu
  • Fangwei Zhang
  • Songlin Sun
Part of the Communications in Computer and Information Science book series (CCIS, volume 320)

Abstract

The distribution preservation is a challenge inthe dimension reduction methods. This paper proposes a distance adaptive embedding method (DAE). The DAE method includes the cosine similarity technology and a new distance transformation function. It has the characteristics of easy handling and strong similarity distinction. The DAE method can make small loss value and good cluster discrimination by using the new distance transformation function in the embedding.The experiment results show that the DAE method has a good performance in distribution preservation, better than the performance of the multidimensional scaling method.

Keywords

dimension reduction clustering distance adaptive embedding 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yanting Niu
    • 1
    • 2
  • Yueming Lu
    • 1
    • 2
  • Fangwei Zhang
    • 3
  • Songlin Sun
    • 1
    • 2
  1. 1.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Key Laboratory of Trustworthy Distributed Computing and Service (BUPT)Ministry of EducationBeijingChina
  3. 3.School of HumanitiesBeijing University of Posts and TelecommunicationsBeijingChina

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