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Optimizing text quantifiers for multivariate loss functions

Academic Article
Publication Date:
2015
abstract:
Quantification - also known as class prior estimation - is the task of estimating the relative frequencies of classes in application scenarios in which such frequencies may change over time. This task is becoming increasingly important for the analysis of large and complex datasets. Researchers from ISTI-CNR, Pisa, are working with supervised learning methods explicitly devised with quantification in mind.
Iris type:
01.01 Articolo in rivista
Keywords:
Text quantification
List of contributors:
Esuli, Andrea; Sebastiani, Fabrizio
Authors of the University:
ESULI ANDREA
SEBASTIANI FABRIZIO
Handle:
https://iris.cnr.it/handle/20.500.14243/258516
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/258516/45625/prod_294303-doc_84459.pdf
Published in:
ERCIM NEWS
Journal
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URL

http://ercim-news.ercim.eu/images/stories/EN100/EN100-web.pdf
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