R help - Jan 2006 - randomForest - classifier switch

Hi
 
I am trying to use randomForest for classification. I am using this
code:
 
> set.seed(71)
> rf.model <- randomForest(similarity ~ ., data=set1[1:100,],
importance=TRUE, proximity=TRUE)
Warning message: 
The response has five or fewer unique values.  Are you sure you want to
do regression? in: randomForest.default(m, y, ...) 
> rf.model
 
Call:
 randomForest(x = similarity ~ ., data = set1[1:100, ], importance TRUE,     
proximity = TRUE)
               Type of random forest: regression
                     Number of trees: 500
No. of variables tried at each split: 10
 
          Mean of squared residuals: 0.1159130
                    % Var explained: 50.8
>
 
As you can see I get a regression model.  How can I make sure I get a
classification model?
 
Thanks .
 
Stephen

-- 



2/01/2006
 

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From: Stephen Choularton
> 
> Hi
>  
> I am trying to use randomForest for classification. I am using this
> code:
>  
> > set.seed(71)
> > rf.model <- randomForest(similarity ~ ., data=set1[1:100,],
> importance=TRUE, proximity=TRUE)
> Warning message: 
> The response has five or fewer unique values.  Are you sure 
> you want to
> do regression? in: randomForest.default(m, y, ...) 
> > rf.model
>  
> Call:
>  randomForest(x = similarity ~ ., data = set1[1:100, ], importance >
TRUE,      proximity = TRUE)
>                Type of random forest: regression
>                      Number of trees: 500
> No. of variables tried at each split: 10
>  
>           Mean of squared residuals: 0.1159130
>                     % Var explained: 50.8
> >
>  
> As you can see I get a regression model.  How can I make sure I get a
> classification model?
By making sure your response variable is a factor, e.g.,

  set1$similarity <- as.factor(set1$similarity)

Andy

  
> Thanks .
>  
> Stephen
> 
> -- 
> 
> 
> 
> 2/01/2006
>  
> 
> 	[[alternative HTML version deleted]]
> 
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