Build an algorithm to predict friendships, then actually use it to meet people
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Re: Build an algorithm to predict friendships, then actually use it to meet people
#2Re: Build an algorithm to predict friendships, then actually use it to meet people
#3Re: Build an algorithm to predict friendships, then actually use it to meet people
#4If this is really a competition (and not just "Here, have fun with our dataset!"), you need to define the rules a little bit more clearly. How are you weighing recall vs. precision? Or are you just looking at % correct labels, where the only two labels possible are "FRIENDS" and "NOT FRIENDS"?
Re: Build an algorithm to predict friendships, then actually use it to meet people
#5Re: Build an algorithm to predict friendships, then actually use it to meet people
#6Hey HN, Grouper founder here. Let me know if you have any questions about the contest.
Re: Build an algorithm to predict friendships, then actually use it to meet people
#7This would be a little more fun if there was a cash prize. No offense meant, groupers look cool, but you'd probably get some more participation that way.
Re: Build an algorithm to predict friendships, then actually use it to meet people
#8That fact that the women are depicted as just three pairs of legs doesn't help, though.
Re: Build an algorithm to predict friendships, then actually use it to meet people
#9Re: Build an algorithm to predict friendships, then actually use it to meet people
#10This is interesting, but given your parameters (predict the most friendships), all you're technically asking for is recall. I'll write an algorithm that has 100% recall: predict that all people become friends with each other. If this is really a competition (and not just "Here, have fun with our dataset!"), you need to define the rules a little bit more clearly. How are you weighing recall vs. precision? Or are you j…
You get 1 point for each friendship that you correctly predict did or did not occur. In the test data set ~50% of pairs became friends, so predicting "everyone became friends" would get 250 points, whereas a perfect algorithm would get 500 points.
I'm updating the README now to make our scoring system more clear.