R help - Mar 2011 - use "caret" to rank predictors by random forest model

Hi,

I'm using package "caret" to rank predictors using random forest
model and draw predictors importance plot. I used below commands:

rf.fit<-randomForest(x,y,ntree=500,importance=TRUE) 
## "x" is matrix whose columns are predictors, "y" is a
binary resonse vector
## Then I got the ranked predictors by ranking
"rf1$importance[,"MeanDecreaseAccuracy"]"
## Then draw the importance plot
varImpPlot(rf.fit)

As you can see, all the functions I used are directly from the package
"randomForest", instead of from "caret". so I'm
wondering if the package "caret" has some functions who can do the
above ranking and ploting.

In fact, I tried functions "train", "varImp" and
"plot" from package "caret", the random forest model that
built by "train" can not be input correctly to "varImp",
which gave error message like "subscripts out of bounds". Also
function "plot" doesn't work neither.

So I'm wondering if anybody has encountered the same problem before, and
could shed some light on this. I would really appreciate your help.

Thanks,
Xiaoqi

It would help if you provided the code that you used for the caret functions.

The most likely issues is not using importance = TRUE in the call to train()

I believe that I've only implemented code for plotting the varImp
objects resulting from train() (eg. there is plot.varImp.train but not
plot.varImp).

Max

On Mon, Mar 7, 2011 at 3:27 PM, Xiaoqi Cui <xcui at mtu.edu>
wrote:
> Hi,
>
> I'm using package "caret" to rank predictors using random
forest model and draw predictors importance plot. I used below commands:
>
> rf.fit<-randomForest(x,y,ntree=500,importance=TRUE)
> ## "x" is matrix whose columns are predictors, "y" is a
binary resonse vector
> ## Then I got the ranked predictors by ranking
"rf1$importance[,"MeanDecreaseAccuracy"]"
> ## Then draw the importance plot
> varImpPlot(rf.fit)
>
> As you can see, all the functions I used are directly from the package
"randomForest", instead of from "caret". so I'm
wondering if the package "caret" has some functions who can do the
above ranking and ploting.
>
> In fact, I tried functions "train", "varImp" and
"plot" from package "caret", the random forest model that
built by "train" can not be input correctly to "varImp",
which gave error message like "subscripts out of bounds". Also
function "plot" doesn't work neither.
>
> So I'm wondering if anybody has encountered the same problem before,
and could shed some light on this. I would really appreciate your help.
>
> Thanks,
> Xiaoqi
>
> ______________________________________________
> R-help at 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.
>


-- 

Max

Thanks for your prompt reply!

You're right, I didn't add the parameter "importance=TRUE"
when I used function "train" to fit the random forest model. Once I
used the above parameter, everything went well. Also the functions
"varImp" and "plot" work well too.

I noticed "caret" is really good at selecting important predictors.
Here I just have another question about using the package "caret" to
select the best subset of predictors. As I know, the function "rfe"
can be used to select the optimal set of important predictors given a series of
sizes of the subsets. I'm wondering if "caret" can automatically
give the best size of the selected subset without user providing the candidate
sizes. Thanks,

Best,

Xiaoqi
----- Original Message -----
From: "Max Kuhn" <mxkuhn at gmail.com>
To: "Xiaoqi Cui" <xcui at mtu.edu>
Cc: r-help at r-project.org
Sent: Monday, March 7, 2011 2:33:06 PM GMT -06:00 US/Canada Central
Subject: Re: [R] use "caret" to rank predictors by random forest model

It would help if you provided the code that you used for the caret functions.

The most likely issues is not using importance = TRUE in the call to train()

I believe that I've only implemented code for plotting the varImp
objects resulting from train() (eg. there is plot.varImp.train but not
plot.varImp).

Max

On Mon, Mar 7, 2011 at 3:27 PM, Xiaoqi Cui <xcui at mtu.edu>
wrote:
> Hi,
>
> I'm using package "caret" to rank predictors using random
forest model and draw predictors importance plot. I used below commands:
>
> rf.fit<-randomForest(x,y,ntree=500,importance=TRUE)
> ## "x" is matrix whose columns are predictors, "y" is a
binary resonse vector
> ## Then I got the ranked predictors by ranking
"rf1$importance[,"MeanDecreaseAccuracy"]"
> ## Then draw the importance plot
> varImpPlot(rf.fit)
>
> As you can see, all the functions I used are directly from the package
"randomForest", instead of from "caret". so I'm
wondering if the package "caret" has some functions who can do the
above ranking and ploting.
>
> In fact, I tried functions "train", "varImp" and
"plot" from package "caret", the random forest model that
built by "train" can not be input correctly to "varImp",
which gave error message like "subscripts out of bounds". Also
function "plot" doesn't work neither.
>
> So I'm wondering if anybody has encountered the same problem before,
and could shed some light on this. I would really appreciate your help.
>
> Thanks,
> Xiaoqi
>
> ______________________________________________
> R-help at 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.
>


-- 

Max