A short tutorial for time series classification and explanation with MrSQM

被引:1
|
作者
Thach Le Nguyen [1 ]
Ifrim, Georgiana [1 ]
机构
[1] Univ Coll Dublin, Dublin, Ireland
基金
爱尔兰科学基金会;
关键词
Time series classification; Feature selection; !text type='Python']Python[!/text; C++; Linear models; Explanation; Saliency map;
D O I
10.1016/j.simpa.2021.100197
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper presents MrSQM, a Python tool for the task of time series classification and explanation. Time series classification is a critical problem not only in scientific research but also in many real-life applications. However, state-of-the-art time series classifiers including deep learning and ensemble architectures are often impractical due to their complexity. MrSQM can provide an alternative lightweight solution, just as accurate but faster, and explainable. The tool is written mainly in C++ but wrapped with Cython to provide a more accessible Python interface.
引用
收藏
页数:3
相关论文
共 50 条
  • [31] Uncertain Time Series Classification
    Mbouopda, Michael Franklin
    PROCEEDINGS OF THE THIRTIETH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2021, 2021, : 4903 - 4904
  • [32] Classification trees for time series
    Douzal-Chouakria, Ahlame
    Amblard, Cecile
    PATTERN RECOGNITION, 2012, 45 (03) : 1076 - 1091
  • [33] Time Series Clustering and Classification
    Chen, Ming
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2020, 115 (531) : 1558 - 1558
  • [34] Bayesian time series classification
    Sykacek, P
    Roberts, S
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 14, VOLS 1 AND 2, 2002, 14 : 937 - 944
  • [35] Time Series Classification with InceptionFCN
    Usmankhujaev, Saidrasul
    Ibrokhimov, Bunyodbek
    Baydadaev, Shokhrukh
    Kwon, Jangwoo
    SENSORS, 2022, 22 (01)
  • [36] On the blind classification of time series
    Bissacco, Alessandro
    Soatto, Stefano
    2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, 2007, : 2578 - +
  • [37] Early classification on time series
    Zhengzheng Xing
    Jian Pei
    Philip S. Yu
    Knowledge and Information Systems, 2012, 31 : 105 - 127
  • [38] Time Series Clustering and Classification
    Vishwakarma, Srishti
    Lyubchich, Vyacheslav
    TECHNOMETRICS, 2021, 63 (03) : 441 - 441
  • [39] Time Series Clustering and Classification
    Tattar, Prabhanjan Narayanachar
    BIOMETRICS, 2020, 76 (04)
  • [40] Deep Learning for Time Series Forecasting: Tutorial and Literature Survey
    Benidis, Konstantinos
    Rangapuram, Syama Sundar
    Flunkert, Valentin
    Wang, Yuyang
    Maddix, Danielle
    Turkmen, Caner
    Gasthaus, Jan
    Bohlke-Schneider, Michael
    Salinas, David
    Stella, Lorenzo
    Aubet, Francois-Xavier
    Callot, Laurent
    Januschowski, Tim
    ACM COMPUTING SURVEYS, 2023, 55 (06)