library(xgboost)

X = as.matrix(train[,-58])
y = train[,58]
numberOfClasses <- max(y) + 1

bst <- xgboost(data = X, label = y, max.depth = 2, eta = 1, nthread = 2, nround = 200, objective = "binary:logistic", verbose = 1)

pred = predict(bst, data.matrix(test[,-58]))
pred = as.numeric(pred > 0.5)
mean(as.numeric(pred > 0.5) != test$spam)