Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Experiences from a Socio-economic Application of Induction Trees

  • Conference paper
Discovery Science (DS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4265))

Included in the following conference series:

  • 1233 Accesses

Abstract

This paper presents a full scaled application of induction trees for non-classificatory purposes. The grown trees are used for highlighting 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. Trees grown by language regions exhibit fundamental cultural differences supporting the hypothesis of cultural models in female participation. The explanatory power of the induced trees is measured with deviance based fit measures.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification And Regression Trees. Chapman and Hall, New York (1984)

    MATH  Google Scholar 

  2. Kass, G.V.: An exploratory technique for investigating large quantities of categorical data. Applied Statistics 29, 119–127 (1980)

    Article  Google Scholar 

  3. Losa, F.B., Origoni, P.: Partecipazione e non partecipazione femminile al mercato del lavoro. Modelli socioculturali a confronto. Il caso della Svizzera italiana nel contesto nazionale. Aspetti statistici, Ufficio cantonale di statistica, Bellinzona (2004)

    Google Scholar 

  4. Losa, F.B., Origoni, P.: The socio-cultural dimension of women’s labour force participation choices in Switzerland. International Labour Review 144, 473–494 (2005)

    Article  Google Scholar 

  5. Murthy, S.K.: Automatic construction of decision trees from data: A multi-disciplinary survey. Data Mining and Knowledge Discovery 2, 345–389 (1998)

    Article  MathSciNet  Google Scholar 

  6. Reyneri, E.: Sociologia del mercato del lavoro. Il Mulino, Bologna (1996)

    Google Scholar 

  7. Ritschard, G.: Computing and using the deviance with classification trees. In: Rizzi, A., Vichi, M. (eds.) COMPSTAT 2006 - Proceedings in Computational Statistics. Springer, Heidelberg (2006)

    Google Scholar 

  8. Ritschard, G., Zighed, D.A.: Goodness-of-fit measures for induction trees. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds.) ISMIS 2003. LNCS (LNAI), vol. 2871, pp. 57–64. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Losa, F.B., Origoni, P., Ritschard, G. (2006). Experiences from a Socio-economic Application of Induction Trees. In: Todorovski, L., LavraÄŤ, N., Jantke, K.P. (eds) Discovery Science. DS 2006. Lecture Notes in Computer Science(), vol 4265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893318_33

Download citation

  • DOI: https://doi.org/10.1007/11893318_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46491-4

  • Online ISBN: 978-3-540-46493-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics