 Validating Tree Descriptions of Women's Labor Participation with Deviance-based CriteriaGilbert Ritschard,
Fabio Losa () and
Origoni Pau
Post-Print from HAL Abstract: This chapter presents a full scaled application of induction trees for non-classificatory purposes. The grown trees are used for high-lighting regional differences in the women's labor participation, by using data from the Swiss Population Census. Hence, the focus is on their descriptive rather than predictive power. A first tree provides evidence for three separate analyses for non-mothers, married or wid-owed mothers, and divorced or single mothers. For each group, trees grown by language regions exhibit fundamental cultural differences supporting the hypothesis of cultural models in female participation. From the methodological standpoint, the main difficulties with such a non-classificatory use of trees have to do with their validation, since 1 the classical classification error rate does not make sense in this setting. We comment on this aspect and propose deviance-based solutions that are both consistent with our non-classificatory usage and easy to compute. Keywords: socio-economic issues; Swiss population; classification trees (search for similar items in EconPapers) Published in John J. McArdle; Gilbert Ritschard. Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences, Routledge, pp.128-149, 2013, 9780415817097 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-01182913 Access Statistics for this paper More papers in Post-Print from HAL |
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