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XEM: An Explainable-by-Design Ensemble Method for Multivariate Time
  Series Classification

XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series Classification

7 May 2020
Kevin Fauvel
Elisa Fromont
Véronique Masson
P. Faverdin
Alexandre Termier
    AI4TS
ArXivPDFHTML

Papers citing "XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series Classification"

3 / 3 papers shown
Title
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies
Lucas Heublein
N. Raichur
Tobias Feigl
Tobias Brieger
Fin Heuer
Lennart Asbach
A. Rügamer
Felix Ott
49
7
0
31 Mar 2025
An Efficient Federated Distillation Learning System for Multi-task Time
  Series Classification
An Efficient Federated Distillation Learning System for Multi-task Time Series Classification
Huanlai Xing
Zhiwen Xiao
R. Qu
Zonghai Zhu
Bowen Zhao
FedML
35
108
0
30 Dec 2021
A Performance-Explainability Framework to Benchmark Machine Learning
  Methods: Application to Multivariate Time Series Classifiers
A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers
Kevin Fauvel
Véronique Masson
Elisa Fromont
AI4TS
41
17
0
29 May 2020
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