Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions-Reference-Cited by-同舟云学术

Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions

Published:2022 Issue: Volume:10 Page:100700-100724
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Theissler Andreas¹^ORCID,Spinnato Francesco²^ORCID,Schlegel Udo³,Guidotti Riccardo⁴^ORCID

Affiliation:

1. Information Systems, Aalen University of Applied Sciences, Aalen, Germany

2. Computer Science, Scuola Normale Superiore, Pisa, Italy

3. Department of Computer and Information Science, University of Konstanz, Konstanz, Germany

4. Department of Computer Science, University of Pisa, Pisa, Italy

Funder

European Commission

Bundesministerium f?r Wissenschaft und Forschung

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09895252.pdf?arnumber=9895252

Reference182 articles.

1. Tslearn, a machine learning toolkit for time series data;tavenard;J Mach Learn Res,2020

2. Sktime: A unified interface for machine learning with time series;löning;arXiv 1909 07872,2019

3. Going beyond visualization. Verbalization as complementary medium to explain machine learning models;sevastjanova;Proc Workshop Vis AI Explainability (VIS),2018

4. pyts: A Python package for time series classification;faouzi;J Mach Learn Res,2020

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