Paper:
Language: English:

A Proposal of Visualization Method for Interpretable Fuzzy Model on Fusion Axes

Kosuke Yamamoto, Tomohiro Yoshikawa, and Takeshi Furuhashi

Department of Computational Science and Engineering, Nagoya University
Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan

Received: July 1, 2005

Accepted: September 13, 2005

Keywords: interpretability, visualization, fusion axis, fuzzy modeling

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.10, No.1 pp. 121-131, 2006

Abstract

Interpretability of fuzzy models has become one of the major topics in the field of fuzzy modeling. Visualization that makes input-output relationships interpretable is effective in extracting useful knowledge from unknown data. This paper presents visualization method that considers the visibility of fuzzy models. This method identifies clusters that have different statistical features, and projects the data to the “fusion axes”, which are linear combinations of the multiple input variables, considering the distribution of each cluster in the projected space. This paper applies the proposed method to artificial data and also to collected data from the mobile robot, and shows that the proposed method can extract useful knowledge from the obtained visible and interpretable models.

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