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Optimization of Combining of Self Organizing Maps and Growing Neural Gas

Abstract : The paper deals with the issue of high dimensional data clustering. One possible way to cluster this kind of data is based on Artificial Neural Networks (ANN) such as Growing Neural Gas (GNG) or Self Organizing Maps (SOM). Parallel modification, Growing Neural Gas with pre-processing by Self Organizing Maps, and its implementation on the HPC cluster is presented in the paper. Some experimental results are also presented. We focus on effective preprocessing for GNG. The clustering is realized on the output layer of SOM and the data for GNG are distributed into parallel processes.
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Lukáš Vojáček, Pavla Dráždilová, Jiří Dvorský. Optimization of Combining of Self Organizing Maps and Growing Neural Gas. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. pp.277-286, ⟨10.1007/978-3-319-45378-1_25⟩. ⟨hal-01637519⟩

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