Publication 4 Probabilistic Measures for Responses of Self−Organizing Map Units
نویسندگان
چکیده
The Self-Organizing Map (SOM) is a widely used data visualization tool in engineering applications. The algorithm performs a non-linear mapping from a highdimensional data space to a low-dimensional space, which is typically a two-dimensional, rectangular grid. This makes it possible to present multidimensional data in two dimensions. Often the model vectors of the SOM and a new data sample need to be compared. The SOM, however, gives no probability measures to determine if the sample belongs to data sets determined by map units. For this purpose a modi ed batch version of reduced kernel density estimator (RKDE) was tested. The results were compared with Gaussian Mixture Model (GMM) and S-Map.
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