Download PDFOpen PDF in browserA simulation experiment on bootstrap inference for Self-Organizing MapsEasyChair Preprint 598210 pages•Date: July 1, 2021AbstractA stochastic simulation study is carried out to learn about quantification of uncertainties for Self-Organizing Maps (SOM). A mixture of Gaussian distributions is assumed as data generating process and the Monte Carlo generated samples are transformed according to the Kohonen (SOM) algorithm. Additionally, the original data matrix is resampled for a bootstrap quantification of parameter estimation uncertainties. Keyphrases: Bootstrap, Self-Organizing Maps, stochastic simulation, uncertainty
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