On Oct 4, 2013, at 2:35 PM, peter dalgaard <pda...@gmail.com> wrote:
> > On Oct 4, 2013, at 21:16 , Mary Kindall wrote: > >> Y[Y < mean(Y)] = 0 #My edit >> Y[Y >= mean(Y)] = 1 #My edit > > I have no clue about gbm, but I don't think the above does what I think you > think it does. > > Y <- as.integer(Y >= mean(Y)) > > might be closer to the mark. Good catch Peter! I didn't pay attention to that initially. Here is an example: set.seed(1) Y <- rnorm(10) > Y [1] -0.6264538 0.1836433 -0.8356286 1.5952808 0.3295078 -0.8204684 [7] 0.4874291 0.7383247 0.5757814 -0.3053884 > mean(Y) [1] 0.1322028 Before changing Y: > Y[Y < mean(Y)] [1] -0.6264538 -0.8356286 -0.8204684 -0.3053884 > Y[Y >= mean(Y)] [1] 0.1836433 1.5952808 0.3295078 0.4874291 0.7383247 0.5757814 However, the incantation that Mary is using, which calculates mean(Y) separately in each call, results in: Y[Y < mean(Y)] = 0 > Y [1] 0.0000000 0.1836433 0.0000000 1.5952808 0.3295078 0.0000000 [7] 0.4874291 0.7383247 0.5757814 0.0000000 # mean(Y) is no longer the original value from above > mean(Y) [1] 0.3909967 Thus: Y[Y >= mean(Y)] = 1 > Y [1] 0.0000000 0.1836433 0.0000000 1.0000000 0.3295078 0.0000000 [7] 1.0000000 1.0000000 1.0000000 0.0000000 Some of the values in Y do not change because the threshold for modifying the values changed as a result of the recalculation of the mean after the first set of values in Y have changed. As Peter noted, you don't end up with a dichotomous vector. Using Peter's method: Y <- as.integer(Y >= mean(Y)) > Y [1] 0 1 0 1 1 0 1 1 1 0 That being said, the original viewpoint stands, which is to not do this due to loss of information. Regards, Marc Schwartz ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
