Using the Distribution of Performance for Studying Statistical NLP Systems and Corpora

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dc.creatorKrymolowski, Yuval
dc.date2001-06-20
dc.date.accessioned2026-07-07T03:17:16Z
dc.date.available2026-07-07T03:17:16Z
dc.descriptionStatistical NLP systems are frequently evaluated and compared on the basis of their performances on a single split of training and test data. Results obtained using a single split are, however, subject to sampling noise. In this paper we argue in favour of reporting a distribution of performance figures, obtained by resampling the training data, rather than a single number. The additional information from distributions can be used to make statistically quantified statements about differences across parameter settings, systems, and corpora.
dc.descriptionTo be presented in ACL/EACL Workshop on Evaluation for Language and Dialogue Systems
dc.identifierhttps://arxiv.org/abs/cs/0106043
dc.identifierhttp://arxiv.org/abs/cs/0106043
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30660
dc.subjectComputation and Language
dc.subjectG.3; I.2.6; I.2.7
dc.titleUsing the Distribution of Performance for Studying Statistical NLP Systems and Corpora
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