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Grassmann clustering

Gruber, Peter and Theis, Fabian J. (2006) Grassmann clustering. In: (Proceedings of ) EUSIPCO 2006: 14th European Signal Processing Conference; September 4 - 8, Florence, Italy. CD-ROM. Piscataway, NJ.

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An important tool in high-dimensional, explorative data mining is given by clustering methods. They aim at identifying samples or regions of similar characteristics, and often code them by a single codebook vector or centroid. One of the most commonly used partitional clustering techniques is the k-means algorithm, which in its batch form partitions the data set into k disjoint clusters by simply ...


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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Dewey Decimal Classification:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Item ID:17088
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