explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning

We propose a framework for interactive and explainable machine learning that enables users to (1) understand machine learning models; (2) diagnose model limitations using different explainable AI methods; as well as (3) refine and optimize the models. Our framework combines an iterative XAI pipeline...

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Veröffentlicht in:	arXiv.org 2019-10
Hauptverfasser:	Spinner, Thilo, Schlegel, Udo, Schäfer, Hanna, El-Assady, Mennatallah
Format:	Artikel
Sprache:	eng
Schlagworte:	Analytics Artificial intelligence Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction Computer Science - Learning Explainable artificial intelligence Interactive systems Iterative methods Machine learning Monitoring Steering mechanisms Workflow
Online-Zugang:	Volltext
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