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Agglomerative MeanShift Clustering

Submitted by on Jul 15 2014 Suggest Revision
By: Xiaotong Yuan
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Resource Type:
Code
License:
Bsd
Language:
Scilab
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None

Description

Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets. For the purpose of algorithm speedup, an agglomerative MS clustering method called Agglo-MS was developed, along with its mode-seeking ability and convergence property analysis. The method is built upon an iterative query set compression mechanism which is motivated by the quadratic bounding optimization nature of MS. The whole framework can be efficiently implemented in linear running time complexity.
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