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An explanation that LASTS: understanding any time series classifier

Spinnato F;
2023
2023
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
ERCIM NEWS
WOS:001038342200010
134
14
16
https://ercim-news.ercim.eu/en134/special/an-explanation-that-lasts-understanding-any-time-series-classifier
XAI framework
LASTS
This article is coauthored with Mirco Nanni, Fosca Giannotti, and Dino Pedreschi (ISTI-CNR, Scuola Normale Superiore, Università di Pisa). Abstract: We present LASTS, an XAI framework that addresses the lack of explainability in black-box time series classifiers. LASTS utilises saliency maps, instance-based explanations and rule-based explanations to provide interpretable insights into the predictions made by these classifiers. LASTS aims to bridge the gap between accuracy and explainability, specifically in critical domains.
3
info:eu-repo/semantics/article
262
Spinnato, F; Guidotti, R; Monreale, A
01 Contributo su Rivista::01.07 Editoriale, Commentario, Contributo a Forum in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/464306
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