Self Organizing Maps: A Robust Implementation
نویسندگان
چکیده
Methods for visualizing multidimensional data are of great interest in computer science and engineering. One popular technique is selforganizing map, a type of neural network, that uses machine learning algorithms to map multidimensional data to a two-dimensional surface. They are widely used for exploratory data analysis and visualization and have been used to perform clustering and classification tasks successfully. This paper builds a robust and extensible self-organizing map implementation capable of producing several visualizations and evaluates the quality of the maps that it generates.
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