Time series classification based on arima and adaboost

Jinghui Wang; Shugang Tang

doi:10.1051/matecconf/202030903024

All issues

Volume 309 (2020)

MATEC Web Conf., 309 (2020) 03024

References

Open Access

Issue		MATEC Web Conf. Volume 309, 2020 2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)


Article Number		03024
Number of page(s)		7
Section		Smart Algorithms and Recognition
DOI		https://doi.org/10.1051/matecconf/202030903024
Published online		04 March 2020

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[1] P. Marteau. TimeWarp Edit Distance with Stiffness Adjustment for Time Series Matching.IEEE Transactions on Pattern Analysis and Machine Intelligence 31,2,306–318. 2008. [CrossRef] [Google Scholar]

[2] Hyndman, Rob J; Athanasopoulos, George. 8.9 Seasonal ARIMA models. Forecasting: principles and practice. oTexts. Retrieved 19 May 2015. [Google Scholar]

[3] Freund, Yoav; Schapire, Robert E. A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting. 1995. [Google Scholar]

[4] D. Goldin and P. Kanellakis, On similarity queries for time-seriesdata: Constraint specification and implementation, 1995, pp. 137–153. [Google Scholar]

[5] Eamonn Keogh, Kaushik Chakrabarti, Michael Pazzani, and Sharad Mehrotra. Dimensionality reduction for fast similarity search in large time series databases. Knowledge and information Systems, 3(3),263–286, 2001 [CrossRef] [Google Scholar]

[6] W.B.H. Ali, R. Nock, M. Barlaud, Boosting Stochastic Newton with Entropy Constraint for Large-Scale Image Classification, International Conference on Pattern Recognition Stockholm Sweden August, pp. 232–237, 2014. [Google Scholar]

[7] Hoang Anh Dau, Eamonn Keogh, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Yanping Chen, Bing Hu, Nuijahan Begum, Anthony Bagnall, Abdullah Mueen and Gustavo Batista (2018). The UCR Time Series Classification Archive. URL https://www.cs.ucr.edu/~eamonn/time_series_data_2018/ [Google Scholar]

[8] Wang, Zhiguang & Yan, Weizhong & Oates, Tim. (2017). Time series classification from scratch with deep neural networks: A strong baseline. 1578–1585. 10.1109/IJCNN.2017.7966039. [Google Scholar]

[9] Bagnall, Anthony, et al. Transformation based ensembles for time series classification. Proceedings of the 2012 SIAM international conference on data mining. Society for Industrial and Applied Mathematics, 2012. [Google Scholar]