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International Conference on Database Systems for Advanced Applications

DASFAA 2020: Database Systems for Advanced Applications pp 717–735Cite as

Enhancing Linear Time Complexity Time Series Classification with Hybrid Bag-Of-Patterns

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 12112)

Abstract

In time series classification, one of the most popular models is Bag-Of-Patterns (BOP). Most BOP methods run in super-linear time. A recent work proposed a linear time BOP model, yet it has limited accuracy. In this work, we present Hybrid Bag-Of-Patterns (HBOP), which can greatly enhance accuracy while maintaining linear complexity. Concretely, we first propose a novel time series discretization method called SLA, which can retain more information than the classic SAX. We use a hybrid of SLA and SAX to expressively and compactly represent subsequences, which is our most important design feature. Moreover, we develop an efficient time series transformation method that is key to achieving linear complexity. We also propose a novel X-means clustering subroutine to handle subclasses. Extensive experiments on over 100 datasets demonstrate the effectiveness and efficiency of our method.

Keywords

  • Time series
  • Classification
  • Bag-Of-Patterns

This work is funded by NSFC Grant 61672161 and Dongguan Innovative Research Team Program 2018607201008. We sincerely thank Dr Hoang Anh Dau from University of California, Riverside for responding to our inquiries on the UCR Archive  [5].

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Notes

  1. 1.

    Here we have ignored the Fungi dataset on which we have obtained abnormally short classification time for BOPF. See  [1] for more on this.

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Author information

Authors and Affiliations

  1. School of Computer Science, Fudan University, Shanghai, China

    Shen Liang

  2. Cyberspace Institute of Advanced Technology (CIAT), Guangzhou University, Guangzhou, China

    Shen Liang & Yanchun Zhang

  3. Institute for Sustainable Industries and Liveable Cities, Victoria University, Melbourne, Australia

    Yanchun Zhang

  4. School of Science, Engineering and Information Technology, Federation University Australia, Ballarat, Australia

    Jiangang Ma

Authors
  1. Shen Liang
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  2. Yanchun Zhang
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  3. Jiangang Ma
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Corresponding author

Correspondence to Yanchun Zhang .

Editor information

Editors and Affiliations

  1. Dankook University, Yongin, Korea (Republic of)

    Yunmook Nah

  2. Peking University, Haidian, China

    Prof. Bin Cui

  3. Sungkyunkwan University, Suwon, Korea (Republic of)

    Sang-Won Lee

  4. Department of System Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong

    Prof. Jeffrey Xu Yu

  5. Kangwon National University, Chunchon, Korea (Republic of)

    Prof. Yang-Sae Moon

  6. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Steven Euijong Whang

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Liang, S., Zhang, Y., Ma, J. (2020). Enhancing Linear Time Complexity Time Series Classification with Hybrid Bag-Of-Patterns. In: Nah, Y., Cui, B., Lee, SW., Yu, J.X., Moon, YS., Whang, S.E. (eds) Database Systems for Advanced Applications. DASFAA 2020. Lecture Notes in Computer Science(), vol 12112. Springer, Cham. https://doi.org/10.1007/978-3-030-59410-7_50

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