classification) ## and provide data and response variable task <- makeClassifTask(data=iris, target="Species") ## 2) Define the learner, use listLearners()[,1] ## Choose a specific algorithm lrn <- ma...classification) ## and provide data and response variable task <- makeClassifTask(data=iris, target="Species") ## 2) Define the learner, use listLearners()[,1] ## Choose a specific algorithm lrn <- makeLearner("classif.ctree") n = nrow(iris) train.set <- sample(n, size=2/3*n) test.set <- setdiff(1:n, train.set) ## 3) Fit the model ## Train the learner on the task using a random subset ## of the data as training set model <- train(lrn, task, subset=train.set) ## 4) Make predictions ## Predict va…
