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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