使用 R 构建决策树时如何解决

Question

我使用 R 构建了一个决策树模型，我想在预测值大于 50% 时向树中添加一个新列并在此列中打印是

N.B：数据集中的目标 coulmun 是布尔值 1 = 心脏病和 0 = 正常

library(rpart)
tree<-rpart(target ~ .,method ='class', data=train)
print(summary(tree))
tree.preds<-predict(tree,test)
print(head(tree.preds))

tree.preds<-as.data.frame(tree.preds)
joiner<-function(x){
  if(x>=0.5)
    return('yes')
    
  else
    return('no')
      
}
tree.preds$disease<-sapply(tree.preds$yes,joiner)

print(head(tree.preds))

此错误出现在运行之后：

Error in `$<-.data.frame`(`*tmp*`, t, value = list()) : 
  replacement has 0 rows, data has 91

Answer 1

您可以使用 ifelse 代替 sapply 的迭代：

library(rpart)

dat = iris[,-5]
dat$target = as.numeric(iris$Species=="versicolor")
idx = sample(nrow(dat),100)
train = dat[idx,]
test = dat[-idx,]

tree = rpart(target ~ .,method ='class', data=train)
tree.preds = data.frame(predict(tree,test))
tree.preds$Species = ifelse(tree.preds[,2]>0.5,"yes","no")

使用 R 构建决策树时如何解决

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