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  4. Outline of an Independent Systematic Blackbox Test for ML-based Systems
 
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July 2024
Conference Paper
Title

Outline of an Independent Systematic Blackbox Test for ML-based Systems

Abstract
This article proposes a test procedure that can be used to test ML models and ML-based systems independently of the actual training process. In this way, the typical quality statements such as accuracy and precision of these models and system can be verified independently, taking into account their black box character and the immanent stochastic properties of ML models and their training data. The article presents first results from a set of test experiments and suggest extensions to existing test methods reflecting the stochastic nature of ML models and ML-based systems.
Author(s)
Wiesbrock, Hans-Werner
Großmann, Jürgen  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Mainwork
Sixth IEEE International Conference on Artificial Intelligence Testing, AITest 2024. Proceedings  
Conference
International Conference on Artificial Intelligence Testing 2024  
Open Access
DOI
10.1109/AITest62860.2024.00009
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • Testing AI Systems

  • Blackbox Test for AI Systems

  • Systematic Evaluation of Training Datasets

  • Probabilistic Modelling

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