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dc.contributor.authorSering, Konstantin
dc.contributor.authorWeitz, Marc
dc.contributor.authorShafaei-Bajestan, Elnaz
dc.contributor.authorKünstle, David-Elias
dc.date.accessioned2023-02-27T09:31:31Z
dc.date.available2023-02-27T09:31:31Z
dc.date.issued2022-11-15
dc.description.abstractThe pyndl package implements Naïve Discriminative Learning (NDL) in Python. NDL is an incremental learning algorithm grounded in the principles of discrimination learning (Rescorla & Wagner, 1972; Widrow & Hoff, 1960) and motivated by animal and human learning research (e.g. Baayen et al., 2011; Rescorla, 1988). Lately, NDL has become a popular tool in language research to examine large corpora and vocabularies, with 750,000 spoken word tokens (Shafaei-Bajestan et al., 2022) and a vocabulary size of 52,402 word types (Sering et al., 2018). In contrast to previous implementations, pyndl allows for a broader range of analysis, including non-English languages, adds further learning rules and provides better maintainability while having the same fast processing speed. As of today, it supports multiple research groups in their work and led to several scientific publications.en_US
dc.description.sponsorshipEUen_US
dc.identifier.citationSering, Weitz, Shafaei-Bajestan, Künstle. pyndl: Naïve discriminative learning in python. Journal of Open Source Software (JOSS). 2022en_US
dc.identifier.cristinIDFRIDAID 2128474
dc.identifier.doi10.21105/joss.04515
dc.identifier.issn2475-9066
dc.identifier.urihttps://hdl.handle.net/10037/28611
dc.language.isoengen_US
dc.publisherOpen Journalsen_US
dc.relation.journalJournal of Open Source Software (JOSS)
dc.relation.projectIDinfo:eu-repo/grantAgreement/ERC/H2020/742545/EU/Wide Incremental learning with Discrimination nEtworks/WIDE/en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titlepyndl: Naïve discriminative learning in pythonen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)