The Many Faces of a Kohonen Map A Case Study: SOM-based Clustering for On-Line Fraud Behavior Classification
نویسندگان
چکیده
The Self-Organizing Map (SOM) is an excellent tool for exploratory data analysis. It projects the input space on prototypes of a low-dimensional regular grid which can be efficiently used to visualize and explore the properties of the data. In this article we present a novel methodology using SOM for exploratory analysis, dimensionality reduction and/or variable selection for a classification problem. The methodology is applied to a real case study and the results are compared with other techniques.
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