Hi,
For fun, I'm trying to throw some horse racing data into either an svm
or lrm model. Curious to see what comes out as there are so many
published papers on this.
One thing I don't know how to do is to standardize the probabilities by
race.
For example, if I train an LRM on a bunch of variable I get a model. I
can then get probability predictions from the model. That works.
It seems to me, that for a given race (8-12 horses) the probabilites of
my predictions should sum to one.
1) Is there some way to train the LRM to evaluate and then model the
subsequent date "per race"?? (Perhaps indicate some kind of grouping
variable?
2) Alternately, if I just run my data through a "standard" LRM, is there
some way to then "normalize" the probabilities in a correct way for each
upcoming race?
I've done some extensive research in this area and would be willing to
discuss more details offline with someone if they could contribute to
the process.
Thanks!!
-N
______________________________________________
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.
