I see what you did there: understanding when to trust a ML model with NOVA

  • In this demo paper we present NOVA, a machine learning and explanation interface that focuses on the automated analysis of social interactions. NOVA combines Cooperative Machine Learning (CML) and explainable AI (XAI) methods to reduce manual labelling efforts while simultaneously generating an intuitive understanding of the learning process of a classification system. Therefore, NOVA features a semi-automated labelling process in which users are provided with immediate visual feedback on the predictions, which gives insights into the strengths and weaknesses of the underlying classification system. Following an interactive and exploratory workflow, the performance of the model can be improved by manual revision of the predictions.

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Author:Tobias BaurORCiDGND, Alexander HeimerlGND, Florian LingenfelserGND, Elisabeth AndréORCiDGND
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/101143
Parent Title (English):2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), Cambridge, UK, 3-6 September 2019
Place of publication:Piscataway, NJ
Type:Conference Proceeding
Year of first Publication:2019
Publishing Institution:Universität Augsburg
Release Date:2023/01/23
First Page:77
Last Page:78
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Menschzentrierte Künstliche Intelligenz
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht