Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems

Despite its great success, machine learning can have its limits when dealing with insufficient training data. A potential solution is the additional integration of prior knowledge into the training process which leads to the notion of informed machine learning . In this paper, we present a structure...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2023-01, Vol.35 (1), p.614-633
Hauptverfasser:	von Rueden, Laura, Mayer, Sebastian, Beckh, Katharina, Georgiev, Bogdan, Giesselbach, Sven, Heese, Raoul, Kirsch, Birgit, Pfrommer, Julius, Pick, Annika, Ramamurthy, Rajkumar, Walczak, Michal, Garcke, Jochen, Bauckhage, Christian, Schuecker, Jannis
Format:	Artikel
Sprache:	eng
Schlagworte:	expert knowledge hybrid informed Knowledge representation Machine learning Mathematical model neuro-symbolic Pipelines prior knowledge survey Systematics Taxonomy Training Training data
Online-Zugang:	Volltext
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