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-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Lopez, Dan
Sent: Wednesday, September 26, 2012 9:05 PM
To: R help (r-help at 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
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