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How Much Can We See? A Note on Quantifying Explainability of Machine
  Learning Models
v1v2 (latest)

How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models

29 October 2019
G. Szepannek
    MILMFAtt
ArXiv (abs)PDFHTML

Papers citing "How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models"

2 / 2 papers shown
Title
Transparency, Auditability and eXplainability of Machine Learning Models
  in Credit Scoring
Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring
Michael Bücker
G. Szepannek
Alicja Gosiewska
P. Biecek
FaML
61
115
0
28 Sep 2020
An Overview on the Landscape of R Packages for Credit Scoring
An Overview on the Landscape of R Packages for Credit Scoring
G. Szepannek
8
3
0
21 Jun 2020
1