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.

   It would be helpful if you could point out if I am missing something.
   Thanks for the help.

Regards,
Shameek Ghosh

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