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Abstract
Behavioral science and machine learning have rapidly progressed in recent years. As there is growing interest among behavioral scholars to leverage machine learning, we present strategies for how these methods that can be of value to behavioral scientists using examples centered on behavioral research.
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; Bollinger, Bryan 4 ; Chaney Allison J B 5 ; Dzyabura Daria 6 ; Etkin, Jordan 5 ; Goldfarb Avi 7 ; Liu, Liu 8 ; Sudhir, K 2 ; Wang, Yanwen 9 ; Wright, James R 10 ; Zhu, Ying 11 1 University of Southern California, Los Angeles, USA (GRID:grid.42505.36) (ISNI:0000 0001 2156 6853)
2 Yale University, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710)
3 Cornell University, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X)
4 New York University, New York City, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753)
5 Duke University, Durham, USA (GRID:grid.26009.3d) (ISNI:0000 0004 1936 7961)
6 New Economic School, Moscow, Russia (GRID:grid.454312.5) (ISNI:0000 0000 9363 5144)
7 University of Toronto, Toronto, Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938)
8 University of Colorado Boulder, Boulder, USA (GRID:grid.266190.a) (ISNI:0000000096214564)
9 University of British Columbia, Vancouver, Canada (GRID:grid.17091.3e) (ISNI:0000 0001 2288 9830)
10 University of Alberta, Edmonton, Canada (GRID:grid.17089.37)
11 University of California San Diego, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)





