Male speed dating
What's nice about a Random Forest is that it can show you the predictor importance estimates based on how error increases if you randomly change the value of particular predictors.If they don't matter, it shouldn't increase the error rate much, right?Does that mean people who made fewer matches were more picky and didn't request another date as often as those who were more successful? match rate - if they correlate, then we should see a diagonal line!Most people are more selective about who they go out with for second date.If you plot to standard deviations of ratings people received, the spread is pretty wide, especially for men.Given that people are not always good at assessing their own attractiveness, how does it affect the ultimate goal - getting matches?You can see a fairly good correlation between Yes and No using those two factors.
Interesting article, but surely the data set would have been more useful to us if they'd been considerate enough to include "matlab programming" and "data analysis" in the interest category ratings. On a more serious note, for histograms with non-uniform bin widths it's generally good practice to scale the areas rather than the heights, so perhaps the pdf normalisation option would be more appropriate. So far I have only one experience getting somewhat positive response from a lady by mentioning "MATLAB", and I think she was an astrophysicist at MIT.Based on those scores, the most important features are: scores indicate how much more attractive the partners were relative to the participants.As you can see, people tend to say yes when their partners are more attractive than themselves regardless of gender.The two most obvious factors in such a decision are how much they liked who they met and how likely they think they will get a "yes" from them.There is no point in asking a person for a second date no matter how much you like him or her when you feel there's no chance of getting a yes.