This. This is what's missing with APM. Not regularization or discussing the best choice of lambdas.permaximum wrote:Still I couldn't find "an easy" way to get that data ready for the regression. It looks I should seperate the predictors(players) for defense and offense and use both offensive and defensive rating as the response.
One Year RAPM and Weighted Ridge Regression
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Re: One Year RAPM and Weighted Ridge Regression
Re: One Year RAPM and Weighted Ridge Regression
That is what J.E. does with RAPM, TheSpiceWeasel.TheSpiceWeasel wrote:This. This is what's missing with APM. Not regularization or discussing the best choice of lambdas.permaximum wrote:Still I couldn't find "an easy" way to get that data ready for the regression. It looks I should seperate the predictors(players) for defense and offense and use both offensive and defensive rating as the response.
Re: One Year RAPM and Weighted Ridge Regression
permaximum wrote:@DSMok1
I just decided to seperate it for defensive-offensive RAPM and compare the results to values in Crow's files and I found out the thing you mentioned. I prepared the bbv.com's data according to this article (http://www.countthebasket.com/blog/2008 ... lus-minus/) for the regression but there are two problems in the article that skew the results a bit. In fact I realized it's wrong from the beginning when I read it carefully and I can't lie it made me angry.
Still I couldn't find "an easy" way to get that data ready for the regression. It looks I should seperate the predictors(players) for defense and offense and use both offensive and defensive rating as the response. Getting that data ready for it means considerable time for me. Is there an easy way I'm missing or that's the only way?
Could you (or someone else) clarify the mistakes in that article?
I barely understand ridge regression and I just installed R for the first time yesterday, but I was basically able to match what you had produced (with a lambda of 108.984). I'm curious what is "wrong" about those results?