Clustering analysis and selforganization Clustering analysis v Hierarchical






















































- Slides: 54
Clustering analysis and self-organization Ø Clustering analysis v Hierarchical algorithm v Partitioning algorithm Ø Self-organization v Kohonen self-organizing algorithm v Elastic nets v Slef-organization using Potts models v Natural elastic nets using Potts models Intelligent Numerical Computation 1
Internet resources: Mixture models: http: //www. csse. monash. edu. au/~dld/mixture. modelling. page. html Self-organization http: //www. cis. hut. fi/research/ A review on clustering http: //www. cse. msu. edu/cgi-user/web/tech/document? ID=450 Intelligent Numerical Computation 2
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Features of clustering techiques Intelligent Numerical Computation 8
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& Intelligent Numerical Computation 23
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Kohonen self-organizing Algorithm Winner Updating Intelligent Numerical Computation 26
Kohonen SOM algorithm in the Euclidean space Intelligent Numerical Computation 27
Intelligent Numerical Computation 28
Neighborhood function Intelligent Numerical Computation 29
Simulation: square array Intelligent Numerical Computation 30
Simulation- linear array Intelligent Numerical Computation 31
Topology preservation Self-organization map of the data matrix Minimal spanning tree of the data matrix Intelligent Numerical Computation 32
Dot-product SOM Intelligent Numerical Computation 33
Learning vector quantization(LVQ) Intelligent Numerical Computation 34
Elastic Net Intelligent Numerical Computation 35
Elastic net algorithm Intelligent Numerical Computation 36
Self-organization using Potts models Math Programming Intelligent Numerical Computation 37
Self-organization using Potts models Energy function Intelligent Numerical Computation 38
Free energy and mean field equations Intelligent Numerical Computation 39
Updating rule Intelligent Numerical Computation 40
Natural elastic nets using Potts models Ø Mixed integer and linear programming Ø The learning method Ø Numerical results Intelligent Numerical Computation 41
A generative model Intelligent Numerical Computation 42
Multivariate Gaussian Intelligent Numerical Computation 43
Potts encoding Intelligent Numerical Computation 44
Log likelihood Intelligent Numerical Computation 45
Fitting a generative model Intelligent Numerical Computation 46
MILP Intelligent Numerical Computation 47
Mean field equations Intelligent Numerical Computation 48
Updating rules Intelligent Numerical Computation 49
Updating rules Intelligent Numerical Computation 50
Numerical procedure Intelligent Numerical Computation 51
Numerical results Intelligent Numerical Computation 52
Natural images Intelligent Numerical Computation 53
Local means Intelligent Numerical Computation 54