1.  Not sure what you want.  What "details" are you looking for exactly?  If 
you call predict(trainset) without the newdata argument, you will get the 
(out-of-bag) prediction of the training set, which is exactly the "predicted"  
component of the RF object.

2. If you set type="votes" and norm.votes=FALSE, you will get the counts 
instead of proportions.

Best,
Andy

-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
Behalf Of Lopez, Dan
Sent: Wednesday, September 26, 2012 9:05 PM
To: R help (r-help@r-project.org)
Subject: [R] Random Forest - Extract

Hello,

I have two Random Forest (RF) related questions.


1.       How do I view the classifications for the detail data of my training 
data (aka trainset) that I used to build the model? I know there is an object 
called predicted which I believe is a vector. To view the detail for my testset 
I use the below-bind the columns together. I was trying to do something similar 
for my trainset  but without putting it through the predict function. Instead 
taking directly from the randomForest which I stored in FOREST_model. I really 
need to get to this information to do some comparison of certain cases.

RF_DTL<-cbind(testset,predict(FOREST_model, testset, type="response"))



2.       In the RF model in R the predict function has three possible 
arguments: "response", "vote" or "prob". I noticed "vote and "prob" are 
identical for all records in my data set. Is this typical? If so then what is 
the point of having these two arguments? Ease of use?

Dan


        [[alternative HTML version deleted]]

______________________________________________
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.
Notice:  This e-mail message, together with any attachme...{{dropped:11}}

______________________________________________
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.

Reply via email to