xgboost.R

train = paint_train %>% select(-logprice)
train.y = paint_train %>% select(logprice) %>% pull()
data.new <- paint_test %>% select(-logprice) %>% data.matrix()
xgb.fit <- xgboost(data = data.matrix(train), 
                   label = train.y, 
                   objective = "reg:linear", 
                   eval_metric = "rmse",
                   max.depth = 10, 
                   eta = 0.05, 
                   nround = 75,
                   verbose =0)

xgb.pred <- exp(predict(xgb.fit, newdata = data.new))