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Journal Article

"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons205908

Müller,  Klaus-Robert
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Fulltext (public)

journal.pone.0181142.pdf
(Publisher version), 8MB

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Citation

Arras, L., Horn, F., Montavon, G., Müller, K.-R., & Samek, W. (2017). "What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. PLoS One, 12(8): e0181142. doi:10.1371/journal.pone.0181142.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002D-DC8E-E
Abstract
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