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This data was gathered from participants in experimental speed dating events from 2002-2004.
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During the events, the attendees would have a four-minute "first date" with every other participant of the opposite sex. At the end of their four minutes, participants were asked if they would like to see their date again. They were also asked to rate their date on six attributes: Attractiveness, Sincerity, Intelligence, Fun, Ambition, and Shared Interests.
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The dataset also includes questionnaire data gathered from participants at different points in the process. These fields include: demographics, dating habits, self-perception across key attributes, beliefs on what others find valuable in a mate, and lifestyle information.
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The binary classification goal is to predict if they were matched or not.
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Source code
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Report
- Machine learning report in PDF format.
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Pickle Maker
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- Store objects into a binary file to reduce execution time.
- numpy
- pandas
- scikit-learn
- matplotlib
- seaborn
- pickle
- python built-in libraries: re, time, itertools
- cleanipynb
cleanipynb will cleanup your jupyter notebook by:
- removing unused imports (globally)
- moving all imports to the first cell and reordering them
- reformatting your code with autopep8
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Published by: Joaquin Vanschoren @ 2016 on https://www.openml.org/d/40536
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Available at:
- Raymond Fisman; Sheena S. Iyengar; Emir Kamenica; Itamar Simonson. Gender Differences in Mate Selection: Evidence From a Speed Dating Experiment. The Quarterly Journal of Economics, Volume 121, Issue 2, 1 May 2006, Pages 673–697, https://doi.org/10.1162/qjec.2006.121.2.673