Zobrazeno 1 - 10 of 88 pro vyhledávání: '"DAAS, PIET"'
1
Report
Leveraging Machine Learning for Official Statistics: A Statistical Manifesto
Autor: Puts, Marco, Salgado, David, Daas, Piet
It is important for official statistics production to apply ML with statistical rigor, as it presents both opportunities and challenges. Although machine learning has enjoyed rapid technological advances in recent years, its application does not poss
Externí odkaz: http://arxiv.org/abs/2409.04365
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2
Report
Bias Correction in Machine Learning-based Classification of Rare Events
Autor: Gubbels, Luuk, Puts, Marco, Daas, Piet
Online platform businesses can be identified by using web-scraped texts. This is a classification problem that combines elements of natural language processing and rare event detection. Because online platforms are rare, accurately identifying them w
Externí odkaz: http://arxiv.org/abs/2407.06212
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3
Report
Unbiased Estimations based on Binary Classifiers: A Maximum Likelihood Approach
Autor: Puts, Marco J. H., Daas, Piet J. H.
Binary classifiers trained on a certain proportion of positive items introduce a bias when applied to data sets with different proportions of positive items. Most solutions for dealing with this issue assume that some information on the latter distri
Externí odkaz: http://arxiv.org/abs/2102.08659
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4
Akademický článek
On the Validity of Using Webpage Texts to Identify the Target Population of a Survey: An Application to Detect Online Platforms.
Autor: Daas, Piet1 (AUTHOR) p.j.h.daas@tue.nl, Hassink, Wolter2,3 (AUTHOR), Klijs, Bart4 (AUTHOR)
Publikováno v: Journal of Official Statistics (JOS). Mar2024, Vol. 40 Issue 1, p190-211. 22p.
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5
Akademický článek
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6
Akademický článek
Identifying Drone Web Sites in Multiple Countries and Languages with a Single Model.
Autor: DAAS, PIET1,2 p.j.h.daas@tue.nl, DE MIGUEL, BLANCA3, DE MIGUEL, MARIA3
Publikováno v: Journal of Data Science. Apr2023, Vol. 21 Issue 2, p225-238. 14p.
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7
Akademický článek
Quality framework for combining survey, administrative and big data for official statistics.
Autor: Gootzen, Yvonne A.P.M.1,2 (AUTHOR) yapm.gootzen@cbs.nl, Daas, Piet J.H.1,2 (AUTHOR), van Delden, Arnout1 (AUTHOR)
Publikováno v: Statistical Journal of the IAOS. 2023, Vol. 39 Issue 2, p439-446. 8p.
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8
Akademický článek
Current challenges and possible big data solutions for the use of web data as a source for official statistics.
Autor: Daas, Piet, Maślankowski, Jacek
Publikováno v: Polish Statistician / Wiadomości Statystyczne; Dec2023, Vol. 68 Issue 12, p49-64, 16p
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9
On the Validity of Using Webpage Texts to Identify the Target Population of a Survey: An Application to Detect Online Platforms
Autor: Daas, Piet, Hassink, Wolter, Klijs, Bart
A statistical classification model was developed to identify online platform organizations based on the texts on their website. The model was subsequently used to identify all (potential) platform organizations with a website included in the Dutch Bu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1687::6f907faec31bd5da51cc896919b7da57
https://hdl.handle.net/10419/272568
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10
Akademický článek
Detecting innovative companies via their website.
Autor: Daas, Piet J. H.1,2 (AUTHOR) pjh.daas@cbs.nl, van der Doef, Suzanne3 (AUTHOR)
Publikováno v: Statistical Journal of the IAOS. 2020, Vol. 36 Issue 4, p1239-1251. 13p. 3 Charts, 1 Graph, 1 Map.
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