Dear community, I don't know which is the proper call for svm at e1071, as I'm obtaining really different results when predicting.
Find attached my data. This is what I'm trying: *TYPE1* mod = svm(train[, 8] ~ . , data= train) pred.svm <- predict (mod, train) error.svm <- train$revenues - pred.svm pred.svm.test <- predict (mod, test) svmPredictionRMSE <- rmse(error.svm) /*0.05239259*/ error.svm.test <- test$revenues - pred.svm.test svmPredictionRMSE.test <- rmse(error.svm.test) /*0.06932511*/ *TYPE2* mod.1 = svm(train[, -8] , train[, 8]) pred.1.svm <- predict (mod.1, train[, -8]) error.1.svm <- train$revenues - pred.1.svm rmse(error.1.svm) /*0.3695311*/ pred.1.svm.test <- predict (mod.1, test[, -8]) error.1.svm.test <- test$revenues - pred.1.svm.test rmse(error.1.svm.test) /*0.412292*/ train.txt <http://r.789695.n4.nabble.com/file/n4740595/train.txt> test.txt <http://r.789695.n4.nabble.com/file/n4740595/test.txt> And rmse: function(error) { sqrt(mean(error^2, na.rm= TRUE)) } I also tried: mod2 = svm(formula = train1[, 8] ~ as.matrix(train1[, -8]), data = train) If this is correct, how do I have to write the corresponding predict? Thanks in advance, -- View this message in context: http://r.789695.n4.nabble.com/svm-e1071-call-different-results-tp4740595.html Sent from the datatable-help mailing list archive at Nabble.com. _______________________________________________ datatable-help mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
