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Parametric action decision trees: Incorporating continuous attribute variables into rule-based models of discrete choice

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  • Arentze, Theo
  • Timmermans, Harry

Abstract

Rule-based models, such as decision trees, are ideally suited to represent discontinuous effects of independent variables on discrete choice behavior in transport or spatial systems. At the same time, however, the models require that continuous attributes, such as for example travel time and travel costs, are discretisized, which may decrease the sensitivity of predictions for policy measures that involve these attributes. To overcome this problem and combine the specific strengths of the rule-based and parametric modeling approaches, this paper introduces a hybrid approach. The so-called parametric action decision tree (PADT) replaces the conventional action-assignment rule of the decision tree by a logit model or any other parametric discrete choice model. The PADT includes alternative-specific constants to take the impact of leaf-node membership into account in addition to terms for the continuous attributes. As an illustration, we show how the approach can be used to incorporate travel-costs sensitivity in Albatross - a rule-based model of activity-travel choice. The results indicate that the enhanced, hybrid model can reproduce realistic ranges of price elasticities of travel demand.

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  • Arentze, Theo & Timmermans, Harry, 2007. "Parametric action decision trees: Incorporating continuous attribute variables into rule-based models of discrete choice," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 772-783, August.
  • Handle: RePEc:eee:transb:v:41:y:2007:i:7:p:772-783
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    1. Gärling, Tommy & Kwan, Mei-Po & Golledge, Reginald G., 1994. "Computational-process modelling of household activity scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 28(5), pages 355-364, October.
    2. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    3. Arentze, Theo A. & Timmermans, Harry J. P., 2004. "A learning-based transportation oriented simulation system," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 613-633, August.
    4. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    5. Cantillo, Víctor & Ortúzar, Juan de Dios, 2005. "A semi-compensatory discrete choice model with explicit attribute thresholds of perception," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 641-657, August.
    6. Elke A L M G Moons & Geert P M Wets & Marc Aerts & Theo A Arentze & Harry J P Timmermans, 2005. "The Impact of Simplification in a Sequential Rule-Based Model of Activity-Scheduling Behavior," Environment and Planning A, , vol. 37(3), pages 551-568, March.
    7. Theo Arentze & Harry Timmermans, 2003. "Measuring the goodness-of-fit of decision-tree models of discrete and continuous activity-travel choice: methods and empirical illustration," Journal of Geographical Systems, Springer, vol. 5(2), pages 185-206, August.
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    7. Gutiérrez-Vargas, Álvaro A. & Meulders, Michel & Vandebroek, Martina, 2023. "Modeling preference heterogeneity using model-based decision trees," Journal of choice modelling, Elsevier, vol. 46(C).
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    10. S. Van Cranenburgh & S. Wang & A. Vij & F. Pereira & J. Walker, 2021. "Choice modelling in the age of machine learning -- discussion paper," Papers 2101.11948, arXiv.org, revised Nov 2021.
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    13. Caspar G. Chorus, 2014. "Capturing alternative decision rules in travel choice models: a critical discussion," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 13, pages 290-310, Edward Elgar Publishing.

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