Interpretable Multivariate Time Series Classification Based on Prototype Learning

Dengjuan Ma, Zhu Wang, Jia Xie, Bin Guo, Zhiwen Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Recently, the classification of multivariate time series has attracted much attention in the field of machine learning and data mining, due to its wide application values in biomedicine, finance, industry and so on. During the last decade, deep learning has achieved great success in many tasks. However, while many studies have applied deep learning to time series classification, few works can provide good interpretability. In this paper, we propose a deep sequence model with built-in interpretability by fusing deep learning with prototype learning, aiming to achieve interpretable classification of multivariate time series. In particular, an input sequence is classified by being compared with a set of prototypes, which are also sequences learned by the developed model, i.e., exemplary cases in the problem domain. We use the matched subset of the MIMIC-III Waveform Database to evaluate the proposed model and compare it with several baseline models. Experimental results show that our model can not only achieve the best performance but also provide good interpretability.

Original languageEnglish
Title of host publicationGreen, Pervasive, and Cloud Computing - 15th International Conference, GPC 2020, Proceedings
EditorsZhiwen Yu, Christian Becker, Guoliang Xing
PublisherSpringer Science and Business Media Deutschland GmbH
Pages205-216
Number of pages12
ISBN (Print)9783030642426
DOIs
StatePublished - 2020
Event15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020 - Xi'an, China
Duration: 13 Nov 202015 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12398 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020
Country/TerritoryChina
CityXi'an
Period13/11/2015/11/20

Keywords

  • Deep learning
  • Interpretable classification
  • Multivariate time series
  • Prototype

Fingerprint

Dive into the research topics of 'Interpretable Multivariate Time Series Classification Based on Prototype Learning'. Together they form a unique fingerprint.

Cite this