Here I’ll address three points: Most of the code that I used is here.The simulation The underlying question that I attempted to address is “Suppose that a speed dating company wanted to organize events with more matches. ” As Ryan Carey pointed out, the model that I developed uses data about other speed dates that participants had been on to predict decisions on a given speed date.You also provided ratings on six attributes about your dates: The participants filled out survey questions when they signed up, including what they were looking for in the opposite sex and what they thought others of their own gender looked for. Let's first find out how successful those speed dating events were.If you take the mean ratings and then subtract the self-rating from the peer rating, you see that participants thought others were more into looks while they were also into sincerity and intelligence. If both you and your partner request another date after the first one, then you have a match.Valentine's day is fast approaching and those who are in a relationship might start thinking about plans. Today's guest blogger, Today's guest blogger, Toshi Takeuchi, explores how you can be successful at speed dating events through data.I recently came across an interesting Kaggle dataset Speed Dating Experiment - What attributes influence the selection of a romantic partner? I never experienced speed dating, so I got curious.But since comments focused on methodology rather than the empirical phenomena, I decided to write about methodology first, so that readers wouldn’t have to disbelief while reading my next post.
In order to make a match, you need to request another date and get that request accepted.
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The number of the first dates varied by the event - on average there were 15, but it could be as few as 5 or as many as 22.
Then you were asked if you would like to meet any of them again.
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