XyGen: Synthetic data generator for feature selection[Formula presented]

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dc.contributor.authorKamalov, Firuz
dc.contributor.authorElnaffar, Said
dc.contributor.authorSulieman, Hana
dc.contributor.authorCherukuri, Aswani Kumar
dc.date.accessioned2023-08-11T11:39:05Z
dc.date.available2023-08-11T11:39:05Z
dc.date.issued2023-03
dc.description.abstractGiven the large number of feature selection algorithms, it has become imperative to have a uniform procedure for evaluating the performance of the algorithms. We propose a library of synthetic datasets designed specifically to test the effectiveness of feature selection algorithms. The datasets are inspired by applications in the field of electronics and have a range of characteristics to provide a variety of test scenarios. The software comes in the form of a Python library with standard interface for loading and generating datasets. Each dataset is implemented as a function that allows control of various parameters of the data. © 2023 The Author(s)
dc.identifier.citationKamalov, F., Elnaffar, S., Sulieman, H., & Cherukuri, A. K. (2023). XyGen: Synthetic data generator for feature selection. Software Impacts, 15, 100485. https://doi.org/10.1016/j.simpa.2023.100485
dc.identifier.issn26659638
dc.identifier.urihttps://doi.org/10.1016/j.simpa.2023.100485
dc.identifier.urihttps://hdl.handle.net/20.500.12519/812
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofseriesSoftware Impacts; Volume 15
dc.rightsThis is an open-access article under Creative Commons Attribution (CC BY 4.0)
dc.rights.holderCopyright : © 2023 The Author(s). Published by Elsevier B.V.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectData mining
dc.subjectFeature selection
dc.subjectMachine learning
dc.subjectSynthetic data
dc.titleXyGen: Synthetic data generator for feature selection[Formula presented]
dc.typeArticle

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