Timing, sequencing and quantum of life course events: a machine learning approach
In this methodological paper we discuss and apply machine learning tech-niques, a core research area in the artificial intelligence literature, to analyse simultaneously timing, sequencing, and quantum of life course events from a comparative perspective. We outline the need for techniques which allow the adoption of a holistic approach to the analysis of life courses, illustrating the specific case of the transition to adulthood. We briefly introduce machine learning algorithms to build decision trees and rule sets and then apply such algorithms to delineate the key features which distinguish Austrian and Ital-ian pathways to adulthood, using Fertility and Family Survey data. The key role of sequencing and synchronisation between events emerges clearly from the methodology used. [AUTHORS]
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Courgeau, Daniel & Lelievre, Eva, 1993. "Event History Analysis in Demography," OUP Catalogue, Oxford University Press, number 9780198287384.
- Lillard, Lee A., 1993. "Simultaneous equations for hazards : Marriage duration and fertility timing," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 189-217, March.
When requesting a correction, please mention this item's handle: RePEc:dem:wpaper:wp-2000-010. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Wilhelm)
If references are entirely missing, you can add them using this form.