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Pattern Classification and Recognition of Movement Behavior of Medaka (Oryzias Latipes) Using Decision Tree

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3614))

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Abstract

Behavioral sequences of the medaka (Oryzias latipes) were continuously investigated through an automatic image recognition system in increasing temperature from 25°C to 35°C. The observation of behavior through the movement tracking program showed many patterns of the medaka. After much observation, behavioral patterns could be divided into basically 4 patterns: active- smooth, active-shaking, inactive-smooth, and inactive-shaking. The “smooth” and “shaking” patterns were shown as normal movement behavior, while the “smooth” pattern was more frequently observed in increasing temperature (35° C) than the “shaking” pattern. Each pattern was classified using a devised decision tree after the feature choice. It provides a natural way to incorporate prior knowledge from human experts in fish behavior and contains the information in a logical expression tree. The main focus of this study was to determine whether the decision tree could be useful in interpreting and classifying behavior patterns of the medaka.

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Lee, S., Kim, J., Baek, JY., Han, MW., Chon, TS. (2005). Pattern Classification and Recognition of Movement Behavior of Medaka (Oryzias Latipes) Using Decision Tree. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_23

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  • DOI: https://doi.org/10.1007/11540007_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28331-7

  • Online ISBN: 978-3-540-31828-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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