Re: [R] Random Forests: Question about R^2

2009-04-21 Thread Liaw, Andy
imitri > > > On Mon, Apr 13, 2009 at 6:22 PM, Liaw, Andy > wrote: > > Apologies: that should have been sum(residual^2)! > > > >> -Original Message- > >> From: Dimitri Liakhovitski [mailto:ld7...@gmail.com] > >> Sent: Monday, April 13, 2009 4

Re: [R] Random Forests: Question about R^2

2009-04-20 Thread Dimitri Liakhovitski
es: that should have been sum(residual^2)! > >> -Original Message- >> From: Dimitri Liakhovitski [mailto:ld7...@gmail.com] >> Sent: Monday, April 13, 2009 4:35 PM >> To: Liaw, Andy >> Cc: R-Help List >> Subject: Re: [R] Random Forests: Question about

Re: [R] Random Forests: Question about R^2

2009-04-13 Thread Liaw, Andy
Apologies: that should have been sum(residual^2)! > -Original Message- > From: Dimitri Liakhovitski [mailto:ld7...@gmail.com] > Sent: Monday, April 13, 2009 4:35 PM > To: Liaw, Andy > Cc: R-Help List > Subject: Re: [R] Random Forests: Question about R^2 > > And

Re: [R] Random Forests: Question about R^2

2009-04-13 Thread Dimitri Liakhovitski
Andy, thank you very much! One clarification question: If MSE = sum(residuals) / n, then in the formula (1 - mse / Var(y)) - shouldn't one square mse before dividing by variance? Dimitri On Mon, Apr 13, 2009 at 10:52 AM, Liaw, Andy wrote: > MSE is the mean squared residuals.  For the training

Re: [R] Random Forests: Question about R^2

2009-04-13 Thread Liaw, Andy
MSE is the mean squared residuals. For the training data, the OOB estimate is used (i.e., residual = data - OOB prediction, MSE = sum(residuals) / n, OOB prediction is the mean of predictions from all trees for which the case is OOB). It is _not_ the average OOB MSE of trees in the forest. I hop

[R] Random Forests: Question about R^2

2009-04-10 Thread Dimitri Liakhovitski
Dear Random Forests gurus, I have a question about R^2 provided by randomForest (for regression). I don't succeed in finding this information. In the help file for randomForest under "Value" it says: rsq: (regression only) - "pseudo R-squared'': 1 - mse / Var(y). Could someone please explain in