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Badgers: generating data quality deficits with Python

2023-07-10Code Available1· sign in to hype

Julien Siebert, Daniel Seifert, Patricia Kelbert, Michael Kläs, Adam Trendowicz

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Abstract

Generating context specific data quality deficits is necessary to experimentally assess data quality of data-driven (artificial intelligence (AI) or machine learning (ML)) applications. In this paper we present badgers, an extensible open-source Python library to generate data quality deficits (outliers, imbalanced data, drift, etc.) for different modalities (tabular data, time-series, text, etc.). The documentation is accessible at https://fraunhofer-iese.github.io/badgers/ and the source code at https://github.com/Fraunhofer-IESE/badgers

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