library(rpart)
library(kernlab)
library(MASS)
library(adabag)
library(caret)
library(randomForest)
library(mlbench)
library(tree)
data(spam)
# drzewa decyzyjne
rows <- sample.int(nrow(spam), size = round(nrow(spam)/3), replace = F)
spam.train <- spam[-rows,]
spam.test <- spam[rows,]
model.rpart <- rpart(type~. , data = spam.train)
plot(model.rpart)
text(model.rpart)
result <- predict(model.rpart, newdata = spam.test[,-58], type = "class")
error <- 1 - sum(result == spam.test[,58])/length(spam.test[,58])
error