Matches in SemOpenAlex for { <https://semopenalex.org/work/W4220976981> ?p ?o ?g. }
- W4220976981 endingPage "100340" @default.
- W4220976981 startingPage "100340" @default.
- W4220976981 abstract "Since its inception, the choice modelling field has been dominated by theory-driven modelling approaches. Machine learning offers an alternative data-driven approach for modelling choice behaviour and is increasingly drawing interest in our field. Cross-pollination of machine learning models, techniques and practices could help overcome problems and limitations encountered in the current theory-driven modelling paradigm, such as subjective labour-intensive search processes for model selection, and the inability to work with text and image data. However, despite the potential benefits of using the advances of machine learning to improve choice modelling practices, the choice modelling field has been hesitant to embrace machine learning. This discussion paper aims to consolidate knowledge on the use of machine learning models, techniques and practices for choice modelling, and discuss their potential. Thereby, we hope not only to make the case that further integration of machine learning in choice modelling is beneficial, but also to further facilitate it. To this end, we clarify the similarities and differences between the two modelling paradigms; we review the use of machine learning for choice modelling; and we explore areas of opportunities for embracing machine learning models and techniques to improve our practices. To conclude this discussion paper, we put forward a set of research questions which must be addressed to better understand if and how machine learning can benefit choice modelling." @default.
- W4220976981 created "2022-04-03" @default.
- W4220976981 creator A5001424439 @default.
- W4220976981 creator A5018529289 @default.
- W4220976981 creator A5049825776 @default.
- W4220976981 creator A5053990407 @default.
- W4220976981 creator A5054417474 @default.
- W4220976981 date "2022-03-01" @default.
- W4220976981 modified "2023-09-30" @default.
- W4220976981 title "Choice modelling in the age of machine learning - Discussion paper" @default.
- W4220976981 cites W1787224781 @default.
- W4220976981 cites W1967444754 @default.
- W4220976981 cites W1984620179 @default.
- W4220976981 cites W1984758736 @default.
- W4220976981 cites W1985101747 @default.
- W4220976981 cites W1990863283 @default.
- W4220976981 cites W1994793669 @default.
- W4220976981 cites W1995500779 @default.
- W4220976981 cites W2005254558 @default.
- W4220976981 cites W2008900804 @default.
- W4220976981 cites W2010334716 @default.
- W4220976981 cites W2016181237 @default.
- W4220976981 cites W2018953326 @default.
- W4220976981 cites W2019402401 @default.
- W4220976981 cites W2021977876 @default.
- W4220976981 cites W2023124912 @default.
- W4220976981 cites W2023662091 @default.
- W4220976981 cites W2024689521 @default.
- W4220976981 cites W2029223998 @default.
- W4220976981 cites W2032793477 @default.
- W4220976981 cites W2037103256 @default.
- W4220976981 cites W2040689732 @default.
- W4220976981 cites W2041946752 @default.
- W4220976981 cites W2044394043 @default.
- W4220976981 cites W2047379699 @default.
- W4220976981 cites W2049869711 @default.
- W4220976981 cites W2050814304 @default.
- W4220976981 cites W2058309190 @default.
- W4220976981 cites W2066895102 @default.
- W4220976981 cites W2077193898 @default.
- W4220976981 cites W2077627452 @default.
- W4220976981 cites W2077678801 @default.
- W4220976981 cites W2081762866 @default.
- W4220976981 cites W2084341220 @default.
- W4220976981 cites W2093584567 @default.
- W4220976981 cites W2101425925 @default.
- W4220976981 cites W2102204929 @default.
- W4220976981 cites W2108658186 @default.
- W4220976981 cites W2109844396 @default.
- W4220976981 cites W2114389382 @default.
- W4220976981 cites W2114706143 @default.
- W4220976981 cites W2129293644 @default.
- W4220976981 cites W2137983211 @default.
- W4220976981 cites W2144439980 @default.
- W4220976981 cites W2145212723 @default.
- W4220976981 cites W2151804157 @default.
- W4220976981 cites W2159094788 @default.
- W4220976981 cites W2160607820 @default.
- W4220976981 cites W2165893637 @default.
- W4220976981 cites W2168175751 @default.
- W4220976981 cites W2176441702 @default.
- W4220976981 cites W2205871979 @default.
- W4220976981 cites W2208550830 @default.
- W4220976981 cites W2261525379 @default.
- W4220976981 cites W2299239789 @default.
- W4220976981 cites W2587359270 @default.
- W4220976981 cites W2587802550 @default.
- W4220976981 cites W2604280479 @default.
- W4220976981 cites W2614794251 @default.
- W4220976981 cites W2616943032 @default.
- W4220976981 cites W2726842553 @default.
- W4220976981 cites W2734890889 @default.
- W4220976981 cites W2748458544 @default.
- W4220976981 cites W2782280549 @default.
- W4220976981 cites W2789212782 @default.
- W4220976981 cites W2792217325 @default.
- W4220976981 cites W2803116794 @default.
- W4220976981 cites W2809088308 @default.
- W4220976981 cites W2810511505 @default.
- W4220976981 cites W2884443195 @default.
- W4220976981 cites W2890187108 @default.
- W4220976981 cites W2896463379 @default.
- W4220976981 cites W2898530914 @default.
- W4220976981 cites W2898738757 @default.
- W4220976981 cites W2898985731 @default.
- W4220976981 cites W2903054425 @default.
- W4220976981 cites W2904450404 @default.
- W4220976981 cites W2909723409 @default.
- W4220976981 cites W2916029038 @default.
- W4220976981 cites W2943216811 @default.
- W4220976981 cites W2945976633 @default.
- W4220976981 cites W2948220358 @default.
- W4220976981 cites W2955954332 @default.
- W4220976981 cites W2964009739 @default.
- W4220976981 cites W2964057784 @default.
- W4220976981 cites W2973461188 @default.
- W4220976981 cites W2980200466 @default.
- W4220976981 cites W2984353870 @default.