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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