尝试在R中创建ROC曲线时，预测函数出错

在对UCI存储库中提供的印度肝脏患者数据集进行分类后，尝试实现ROC曲线。得到一个错误。下面是R中的代码，后面是错误，后面是数据集头部的dput

代码

数据集

structure(list(age = c(55L, 48L, 14L, 17L, 40L, 37L), gender = c(0L, 
0L, 0L, 0L, 1L, 0L), TB = c(0.9, 2.4, 0.9, 0.9, 0.9, 0.7), DB = c(0.2, 
1.1, 0.3, 0.2, 0.3, 0.2), Alkphos = c(116L, 554L, 310L, 224L, 
293L, 235L), SGPT = c(36L, 141L, 21L, 36L, 232L, 96L), sgot = c(16L, 
73L, 16L, 45L, 245L, 54L), TP = c(6.2, 7.5, 8.1, 6.9, 6.8, 9.5
), ALB = c(3.2, 3.6, 4.2, 4.2, 3.1, 4.9), AG = c(1, 0.9, 1, 1.55, 
0.8, 1), Class = structure(c(2L, 1L, 2L, 1L, 1L, 1L), .Label = c("One", 
"Two"), class = "factor")), .Names = c("age", "gender", "TB", 
"DB", "Alkphos", "SGPT", "sgot", "TP", "ALB", "AG", "Class"), row.names =    c(216L, 
405L, 316L, 103L, 20L, 268L), class = "data.frame")

---

我可以得到ROC曲线，但现在我对它的解释感到困惑。需要进一步的帮助。

问题是当

prediction（）

查找数值向量时，

prob

是一个因子

SVM自然输出类预测，但您可以覆盖它并使用

#svm here, note the probability=TRUE
svmmodel<-svm(Class~.,train,
              kernel="sigmoid", probability = TRUE)

## In the ?predict.svm you can see probability = TRUE is needed to output probability
## type="repsonse" and type = "prob" would do nothing. 
pred.output <-predict(svmmodel,test,probability = TRUE)

## It outputs the probabilities as an attribute, so you need to go in an grab them
prob <- attr(pred.output, "probabilities")[,2]


pred <- prediction(prob, test$Class) #Now this works

#这里，请注意概率=TRUE
svmmodel问题在于当
prediction（）
查找数值向量时，
prob
是因子

SVM自然输出类预测，但您可以覆盖它并使用

#svm here, note the probability=TRUE
svmmodel<-svm(Class~.,train,
              kernel="sigmoid", probability = TRUE)

## In the ?predict.svm you can see probability = TRUE is needed to output probability
## type="repsonse" and type = "prob" would do nothing. 
pred.output <-predict(svmmodel,test,probability = TRUE)

## It outputs the probabilities as an attribute, so you need to go in an grab them
prob <- attr(pred.output, "probabilities")[,2]


pred <- prediction(prob, test$Class) #Now this works

#这里，请注意概率=TRUE
svmmodel
#svm here, note the probability=TRUE
svmmodel<-svm(Class~.,train,
              kernel="sigmoid", probability = TRUE)

## In the ?predict.svm you can see probability = TRUE is needed to output probability
## type="repsonse" and type = "prob" would do nothing. 
pred.output <-predict(svmmodel,test,probability = TRUE)

## It outputs the probabilities as an attribute, so you need to go in an grab them
prob <- attr(pred.output, "probabilities")[,2]


pred <- prediction(prob, test$Class) #Now this works