https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#Head https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ http://www.nanopub.org/nschema#hasAssertion https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ http://www.nanopub.org/nschema#hasProvenance https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#provenance https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#pubinfo https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion http://id.crossref.org/issn/2451-8492 http://purl.org/dc/terms/title Data Science https://doi.org/10.3233/DS-230059 http://purl.org/dc/terms/abstract Measuring data drift is essential in machine learning applications where model scoring (evaluation) is done on data samples that differ from those used in training. The Kullback-Leibler divergence is a common measure of shifted probability distributions, for which discretized versions are invented to deal with binned or categorical data. We present the Unstable Population Indicator, a robust, flexible and numerically stable, discretized implementation of Jeffrey's divergence, along with an implementation in a Python package that can deal with continuous, discrete, ordinal and nominal data in a variety of popular data types. We show the numerical and statistical properties in controlled experiments. It is not advised to employ a common cut-off to distinguish stable from unstable populations, but rather to let that cut-off depend on the use case. https://doi.org/10.3233/DS-230059 http://purl.org/dc/terms/date 2024 https://doi.org/10.3233/DS-230059 http://purl.org/dc/terms/hasPart https://w3id.org/kpxl/ios/ds/np/RA4SqymT32eltSYbr41lDKMBV3Zr8nEBEXRFhfOrN6f3k https://doi.org/10.3233/DS-230059 http://purl.org/dc/terms/isPartOf http://id.crossref.org/issn/2451-8492 https://doi.org/10.3233/DS-230059 http://purl.org/dc/terms/title Measuring Data Drift with the Unstable Population Indicator https://doi.org/10.3233/DS-230059 http://purl.org/pav/authoredBy https://orcid.org/0000-0003-2581-8370 https://doi.org/10.3233/DS-230059 http://purl.org/pav/authoredBy https://orcid.org/0009-0003-5030-0108 https://doi.org/10.3233/DS-230059 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/ResourcePaper https://orcid.org/0000-0003-2581-8370 http://schema.org/affiliation https://ror.org/04dkp9463 https://orcid.org/0000-0003-2581-8370 http://schema.org/affiliation https://ror.org/05xvt9f17 https://orcid.org/0000-0003-2581-8370 http://schema.org/email datascience@marcelhaas.com https://orcid.org/0000-0003-2581-8370 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person https://orcid.org/0000-0003-2581-8370 http://xmlns.com/foaf/0.1/name Marcel R. Haas https://orcid.org/0009-0003-5030-0108 http://schema.org/affiliation https://ror.org/04b8v1s79 https://orcid.org/0009-0003-5030-0108 http://schema.org/affiliation https://ror.org/04dkp9463 https://orcid.org/0009-0003-5030-0108 http://schema.org/email L.Sibbald@tilburguniversity.edu https://orcid.org/0009-0003-5030-0108 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person https://orcid.org/0009-0003-5030-0108 http://xmlns.com/foaf/0.1/name Lisette Sibbald https://ror.org/04b8v1s79 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Organization https://ror.org/04b8v1s79 http://xmlns.com/foaf/0.1/name Department of Methodology and Statistics and Department of Cognitive Neuropsychology, Tilburg University, Prof. Cobbenhagenlaan 125, 5037 DB Tilburg, The Netherlands https://ror.org/04dkp9463 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Organization https://ror.org/04dkp9463 http://xmlns.com/foaf/0.1/name Business Intelligence, University of Amsterdam, Spui 21, 1012WX Amsterdam, The Netherlands https://ror.org/05xvt9f17 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Organization https://ror.org/05xvt9f17 http://xmlns.com/foaf/0.1/name Public Health and Primary Care, Leiden University Medical Center, Albinusdreef 2, The Netherlands https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#provenance https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion http://www.w3.org/ns/prov#wasAttributedTo https://orcid.org/0000-0003-2581-8370 https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion http://www.w3.org/ns/prov#wasAttributedTo https://orcid.org/0009-0003-5030-0108 https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#pubinfo https://orcid.org/0000-0002-1267-0234 http://xmlns.com/foaf/0.1/name Tobias Kuhn 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