The impact of learning parameters on Bayesian self-organizing maps: An empirical study. Abstract: The Bayesian self-organizing map (BSOM) algorithm is an ...
The impact of learning parameters on Bayesian self-organizing maps: An empirical study ... Bayesian learning for self-organising maps · H. YinN. Allinson.
Abstract—The Bayesian self-organizing map (BSOM) algo- rithm is an extended self-organizing learning process, which uses the neurons' estimated posterior ...
Based on the analysis of two synthetic datasets, this paper investigates the impact of the selection of learning parameters such as the learning rates, the ...
Guo, X., Wang, H., & Glass, DH. (2011). The impact of learning parameters on Bayesian self-organizing maps: An empirical study. In Unknown Host Publication ...
Jun 18, 2020 · Bibliographic details on The impact of learning parameters on Bayesian self-organizing maps: An empirical study.
In this study, we implemented an adaptation of the model for performing unsupervized and supervised classification. In order to determine the optimal number of ...
The impact of learning parameters on Bayesian self-organizing maps: An empirical study ... Bayesian learning for self-organising maps · H. YinN. Allinson.
In this paper, we introduce to Bayesian Learning for Self Organizing Maps(BLSOM) which combines self organizing maps with Bayesian learning. So it supports ...
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Mar 29, 2022 · Self-organizing maps and Bayesian networks in organizational modelling: A case study in innovation projects management.