Mar 2, 2022 · This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data.
Sep 8, 2024 · This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data, on a range ...
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data · Oscar Giles, Kasra Hosseini, +13 authors. Sebastian ...
Mar 2, 2022 · This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data, on a range ...
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data · no code implementations • 2 Mar 2022 • Oscar Giles, Kasra ...
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How is synthetic data different from anonymized data?
This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data, on a range of artificially ...
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data · no code implementations • 2 Mar 2022 • Oscar Giles, Kasra ...
The aim of this study is to investigate how trustworthy are group differences discovered by independent sample tests from DP-synthetic data.
This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data, on a range of artificially ...
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. O Giles, K Hosseini, G Mingas, O Strickson, L Bowler, CR ...