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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