Finding fuzzy descriptions using SOMs
|Titel||Finding fuzzy descriptions using SOMs|
Self Organizing Maps (SOMs) are often used to analyze and visualize great datasets. Though they ca show neighborhood relation (and clusters) in a very good way, they lack a natural description of the data points. On the other hand, traditional inductive learning methods that are able to gain more descriptive results, misconduct when applied to big and noisy data.In this paper we will present an combined approach, where SOMs are used to smooth the input data and to reduce the number of samples, while high sophisticated inductive learning methods are used to create a set of fuzzy rules, to describe the dataset in a human-like manner.