dwdm3

data = iris
head(data)

sampler = sample(1:nrow(data), size = 0.9*nrow(data), replace = FALSE)
training_data = data[sampler,]
testing_data = data[-sampler,]

# test_data_label = testing_data[,5]
# training_data_label = training_data[,5]
#
# test_data = testing_data[,-5]
# training_data = training_data[,-5]

library(rattle)
library(rpart)
library(rpart.plot)

model = rpart(training_data$Species~., data=training_data, minsplit=2)
fancyRpartPlot(model)

prediction = predict(model, testing_data[,-5])