Deducing neighborhoods of classes from a fitted model

In todays world the request for very complex models for huge data sets is rising steadily. The problem with these models is that by raising the complexity of the models, it gets much harder to interpret them. The growing field of \emph{interpretable machine learning} tries to make up for the lack of...

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Veröffentlicht in:	arXiv.org 2020-09
Hauptverfasser:	Gerharz, Alexander, Groll, Andreas, Schauberger, Gunther
Format:	Artikel
Sprache:	eng
Schlagworte:	Complexity Data points Machine learning
Online-Zugang:	Volltext
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