Thanks again Max - a great time saver this is.
Now just for my sanity, if I use glm.fit to build a model where I have the
matrices, how do I then use the predict function without getting an error
message?
> LOGISTIC_model1 <- glm.fit(mdrrDescr,mdrrClass,
> family=binomial(link="logit"))
Warning messages:
1: glm.fit: algorithm did not converge
2: glm.fit: fitted probabilities numerically 0 or 1 occurred
> predict(LOGISTIC_model1)
Error in UseMethod("predict") :
no applicable method for 'predict' applied to an object of class
"c('double', 'numeric')"
Secondly, caret acts as a nice wrapper to protect me from all this, and it
does the resampling to give me an idea of the expected model fit. If I was
doing a parameter search, would it do all this resampling for each
combination of parameters? Now if I just want to build a model and not worry
about all the resampling (in my case I just want a set of baseline
predictions to compare various variable selections methods against) it would
be nice if there was a simple option to turn off the resampling.
--
View this message in context:
http://r.789695.n4.nabble.com/caret-prevent-resampling-when-no-parameters-to-find-tp3488761p3489020.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
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.
