Techniques for Spectral Clustering

نویسندگان

  • Pejus Das
  • Mathew Beal
چکیده

Spectral techniques, off late, have been in limelight in the machine learning community and has drawn attention of many serious machine learners. They are being used in a variety of applications like gene clustering, document analysis, image segmentation, dimensionality reduction etc. They are very simple to understand and provide highly accurate results even for difficult clustering problems. Due to their rise in popularity and their importance in every machine learners life we present some spectral clustering techniques available in the literature. We draw similarities between them and try to portray the central idea of spectral clustering. This paper can be thought of as a headway into this interesting and upcoming field.

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تاریخ انتشار 2006