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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/7965

Title: Nonlinear models for determining mode choice - (Accuracy is not always the optimal goal)
Authors: MOONS, Elke
WETS, Geert
Issue Date: 2007
Series/Report: Lecture Notes in Computer Science, 4874
Abstract: Due to the increasing complexity in transportation systems, one needs to search for different ways to model the separate components of these systems. A general transportation system comprises components/models concerning mode choice, travel duration, trip distance, departure time, accompanying individuals, etc. This paper tries to discover whether semi- and nonlinear models bring an added value to transportation analysis in general and mode choice modelling in particular. Linear (logistic regression), semi-linear (multiple fractional polynomials) and nonlinear (support vector machines and classification and regression trees) models are applied to several binary settings and compared to each other based on sensitivity (i.e. the proportion of positive cases that are predicted correctly). In general, one can state that on skewed data sets, linear and semi-linear models tend to perform better, whereas on more balanced data sets both nonlinear models yield better results. Future research will take a closer look at other extensions of the well-established linear regression model.
Notes: Hasselt Univ, Transportat Res Inst, Diepenbeek, B-3590 Belgium.Moons, E, Hasselt Univ, Transportat Res Inst, Sci Pk 5-6, Diepenbeek, B-3590 Belgium.
URI: http://hdl.handle.net/1942/7965
DOI: 10.1007/978-3-540-77002-2_16
ISI #: 000252074800016
ISBN: 978-3-540-77000-8
ISSN: 0302-9743
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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