Hi,
I have a data.frame with dimension 336x336 called *training*, and another one
called *observation* which is 336x1. I combined them as one table using
table=data.frame(training, observation). table now has 336x337 dimension with
the last column as the observation to learn using the training data of the rest
of the column in the table. For prediction, i combined the testing data and
observation and pass it like predict(model,testingWTesingObservation)
I've used the formula: rpart(table[,337] ~ ., data=table) or svm(table[,337] ~
., data=table). I recently discovered that this formulation produces different
model from the: svm(training, observation) formulation. Which is correct and
why one of them is not correct? I thought that syntactically, both are the
same. I hope that R should be able to detect the error in one of the
formulation to avoid the possibility of using it.
Regards,
Paul
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