On Mar 8, 2012, at 5:10 AM, shameek ghosh wrote:
Sir,
This query is related to randomForest regression using R.
I have a dataset called qsar.arff which I use as my training set
and
then I run the following function -
rf=randomForest(x=train,y=trainy,xtest=train,ytest=trainy,ntree=500)
where train is a matrix of predictors without the column to be
predicted(the target column), trainy is the target column.I feed the
same
data for xtest and ytest too as shown.
On verifying I found, rf$mse[500] and rf$test$mse[500] are
different(the r-squares are also different).The predicted values of
the
training target column and testing target column are also different.
Should this happen , since I am using the training dataset as the
testing dataset? I expected that the test and training predictions
would be
the same.
My inference from its name _random_Forest, was that it was _not_
"deterministic forest".
--
David Winsemius, MD
West Hartford, CT
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