Fractal fuzzy decision-making: what is the adequate dimension for self-organizing maps?

We describe a new methodology, based on resources of fractal dimension theory and fuzzy approximated reasoning, to determine the adequate dimension for the output space of self-organizing maps (SOM). This approach considers the dataset under analysis and proposes the dimension that best satisfies th...

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Bibliographic Details
Main Authors: Peres, S.M., Netto, M.Lde.A.
Format: Conference Proceeding
Language:English
Subjects:
Aerospace industry
Applied sciences
Artificial intelligence
Automation
Computer industry
Computer science
control theory
systems
Data analysis
Data mining
Decision making
Distortion measurement
Exact sciences and technology
Fractals
Fuzzy reasoning
Self organizing feature maps
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Summary:We describe a new methodology, based on resources of fractal dimension theory and fuzzy approximated reasoning, to determine the adequate dimension for the output space of self-organizing maps (SOM). This approach considers the dataset under analysis and proposes the dimension that best satisfies the dilemma: to maximize the reduction of dimension and to minimize the topographic distortions - measured with the topographic product. In order to reach this objective, we create the "significant fractal fuzzy dimension measure" as a variation of a fractal dimension measure.
DOI:10.1109/NAFIPS.2004.1337378