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OUTLIER DETECTION IN SELF-ORGANIZING MAPS AND THEIR QUALITY ESTIMATION
2018
Neural Network World
In the paper, an algorithm that allows to detect and reject outliers in a self-organizing map (SOM) has been proposed. SOM is used for data clustering as well as dimensionality reduction and the results obtained are presented in a special graphical form. To detect outliers in SOM, a genetic algorithm-based travelling salesman approach has been applied. After outliers are detected and removed, the SOM quality has to be estimated. A measure has been proposed to evaluate the coincidence of data
doi:10.14311/nnw.2018.28.006
fatcat:wq7wz7u5yngjrnueuwpovgeljq