Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery

Robust feature selection is vital for creating reliable and interpretable Machine Learning (ML) models. When designing statistical prediction models in cases where domain knowledge is limited and underlying interactions are unknown, choosing the optimal set of features is often difficult. To mitigat...

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Hauptverfasser:	S, Saranya Ganesh, Beucler, Tom, Tam, Frederick Iat-Hin, Gomez, Milton S, Runge, Jakob, Gerhardus, Andreas
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Physics - Atmospheric and Oceanic Physics Physics - Computational Physics Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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