Nanopublication for Data Science
Nanopublication ⓘ A nanopublication contains as main content a statement in the assertion part (shown in blue) encoded in a way that computers can understand. It is expressed as one or more subject-relation-object structures, each shown on a separate line, where the identifier of the subject (left) is connected to the identifier of the object (right) via the identifier of the relation type (middle).
https://doi.org/10.3233/DS-230059
doi:10.3233/DS-230059
http://purl.org/dc/terms/abstract
has the abstract
(this is a literal)
"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."
.
The journal with ISSN
http://id.crossref.org/issn/2451-8492
2451-8492
http://purl.org/dc/terms/title
has the title
(this is a literal)
"Data Science"
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/
https://orcid.org/0000-0003-2581-8370
0000-0003-2581-8370
.
This is the identifier for the assertion of this nanopublication.
https://w3id.org/kpxl/ios/ds/np/RAp2-E77MOiPhLIbTOtkjV7l_4y1kYc63ZhZaflJ547FQ#assertion
The assertion above
http://www.w3.org/ns/prov#wasAttributedTo
is attributed to
https://orcid.org/
https://orcid.org/0009-0003-5030-0108
0009-0003-5030-0108
.
This nanopublication has a newer version.
Type Description ⓘ This is the description of the type this nanopublication belongs to.
Reactions ⓘ Anyone can write reactions to this nanopublication, including the Data Science reviewers and editors. When a new reaction is published, it can take a minute or two before it shows up here (after refreshing 🗘). 🗘
(no reactions yet)
Help
Don't hesitate to open a support ticket if you have any questions or problems, no matter how trivial or how complex.