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040 |aCaOODSP|beng|erda|cCaOODSP
043 |an-cn---
0861 |aCS11-522/2024-1-10E-PDF
1001 |aEvans, Justin, |eauthor.
24510|aLife in the FastText lane : |bharnessing linear programming constrained machine learning for classifications revision / |cby Justin Evans and Laura Wile.
2461 |iAt head of title: |aProceedings of Statistics Canada Symposium 2024 : |bthe future of official statistics
264 1|a[Ottawa] : |bStatistics Canada = Statistique Canada, |cSeptember 8, 2025.
300 |a1 online resource (8 unnumbered pages) : |bgraphs.
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
4901 |a[Statistics Canada international symposium series : proceedings], |x1709-8211
500 |aTitle from cover.
500 |aIssued also in French under title: Filer sur la voie du fastText : exploiter l'apprentissage automatique restreint par programmation linéaire pour réviser les classifications.
504 |aIncludes bibliographical references.
5203 |a"Statistics Canada's Labour Force Survey (LFS) plays an essential role in the estimation of labour market conditions in Canada. Periodically, LFS revises its data to the most recent industry and occupational classification versions. Differences in versions can be extensive, including high-level and unit-group structural changes, creations, deletions, split-offs and combination of classification units (classes). Historically, to reconcile split-off classes - where one class splits into multiple classes - a sample of LFS split-off records would be manually recoded to the new classification version. Based on the split-off proportion observed in the recoded sample, a random allocation method would be applied on all data to reflect the changing Canadian labour market over time. This article proposes using machine learning (fastText), constrained to split-off proportions using linear programming, to revise industry and occupation classifications in LFS. The hybrid framework benefits from a text-based revision mechanism while adhering to traditional proportions driven estimates, thus ensuring a minimal impact on the comparability of published labour market indicators"--Abstract, page [2].
650 0|aMachine learning.
650 0|aLabor supply|zCanada|vStatistics.
650 0|aOccupations|zCanada|vClassification.
655 7|aStatistics|2lcgft
7102 |aStatistics Canada, |eissuing body.
77508|tFiler sur la voie du fastText : |w(CaOODSP)9.966445
830#0|aStatistics Canada international symposium series - proceedings,|x1709-8211|w(CaOODSP)9.505681
85640|qPDF|s521 KB|uhttps://publications.gc.ca/collections/collection_2026/statcan/11-522-x/CS11-522-2024-1-10-eng.pdf
986 |a11-522-X