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Data Treatment Effects on Classification Accuracies of Bipedal Running and Walking Motions

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Recent Advances on Soft Computing and Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 287))

Abstract

Many real-world data can be irrelevant, redundant, inconsistent, noisy or incomplete. To extract qualitative data for classification analysis, efficient data preprocessing techniques such as data transformation, data compression, feature extraction and imputation are required. This study investigates three data treatment approaches: randomization; attribute elimination and missing values imputation on bipedal motion data. The effects of data treatment were examined on classification accuracies to retrieve informative attributes. The analysis is performed on bipedal running and walking motions concerning the human and ostrich obtained from public available domain and a real case study. The classification accuracies were tested on seven classifier categories aided by the WEKA tool. The findings show enhancements in classification accuracies for treated dataset in bipedal run and walk with respective enhancements of 3.21% and 2.29% in treated data compared to the original. The findings support the integration of data randomization and selective attribute elimination treatment for better effects in classification analysis.

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Universiti Sains Malaysia, 14300, Nibong Tebal, Seberang Perai Selatan, Penang, Malaysia

    Wei Ping Loh & Choo Wooi H‘ng

Authors
  1. Wei Ping Loh
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  2. Choo Wooi H‘ng
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Corresponding author

Correspondence to Wei Ping Loh .

Editor information

Editors and Affiliations

  1. Department of Information System Faculty of Comp. Sci. & Info. Tech., University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Faculty of Comp. Sci. and Info. Tech, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

    Rozaida Ghazali

  3. Faculty of Comp. Sci. and Info. Tech., Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

    Mustafa Mat Deris

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© 2014 Springer International Publishing Switzerland

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Loh, W.P., H‘ng, C.W. (2014). Data Treatment Effects on Classification Accuracies of Bipedal Running and Walking Motions. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_45

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  • DOI: https://doi.org/10.1007/978-3-319-07692-8_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07691-1

  • Online ISBN: 978-3-319-07692-8

  • eBook Packages: EngineeringEngineering (R0)

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