Linear Fuzzy Clustering Based on Least Absolute Deviations

Katsuhiro Honda; Nobuhiro Togo; Hidetomo Ichihashi

doi:10.11499/sicep.2002.0.513.0

SICE Annual Conference 2002

DOI https://doi.org/10.11499/sicep.2002.0.513.0

Conference information

Host: The Society of Instrument and Control Engineers

Co-host: IEEE/Industiral Electronic Society, IEEE/Robotics and Automation Society, IEEE/Control System Society

Linear Fuzzy Clustering Based on Least Absolute Deviations

Katsuhiro Honda, Nobuhiro Togo, Hidetomo Ichihashi

Author information

Keywords: Fuzzy clustering, Least absolute deviation, Missing value

CONFERENCE PROCEEDINGS FREE ACCESS

Pages 513

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Abstract

This paper proposes a technique of linear fuzzy clustering based on least absolute deviations. The least absolute deviations adopted in the method provide robust clustering results that are free from the influence of outliers. The simplicity of the proposed objective function makes it possible to handle missing values by simply ignoring only the missing coordinates.

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