r - 在 SVM 中绘制 Roc 曲线

Question

我正在尝试为 SVM 创建 ROC 曲线，这是我使用的代码:

#learning from training
#tuned <- tune.svm(y~., data=train, gamma = 10^(-6:-1), cost = 10^(1:2))
summary(tuned)


svmmodel<-svm(y~., data=train, method="C-classification",
              kernel="radial", gamma = 0.01, cost = 100,cross=5, probability=TRUE) 

svmmodel

#predicting the test data
svmmodel.predict<-predict(svmmodel,subset(test,select=-y),decision.values=TRUE)
svmmodel.probs<-attr(svmmodel.predict,"decision.values")
svmmodel.class<-predict(svmmodel,test,type="class")
svmmodel.labels<-test$y
#analyzing result
svmmodel.confusion<-confusion.matrix(svmmodel.labels,svmmodel.class)
svmmodel.accuracy<-prop.correct(svmmodel.confusion)

#roc analysis for test data
svmmodel.prediction<-prediction(svmmodel.probs,svmmodel.labels)
svmmodel.performance<-performance(svmmodel.prediction,"tpr","fpr")
svmmodel.auc<-performance(svmmodel.prediction,"auc")@y.values[[1]]

但是ROC曲线的问题是这样的:

Answer 1

我在MATLAB - generate confusion matrix from classifier回答了类似的问题
通过使用上面链接中给出的代码，如果您得到如图所示的反向 ROC 曲线，则替换以下行(在链接中给出的代码中):
1. 替换链接中给出的代码中的行。

b_pred = (tot_op>=th_vals(i,1)); 

由

b_pred = (tot_op<=th_vals(i,1));  

2.更换线路

AUC = sum(0.5*(sens(2:end)+sens(1:end-1)).*(cspec(2:end) - cspec(1:end-1))); 

由

AUC = sum(0.5*(sens(2:end)+sens(1:end-1)).*(cspec(1:end-1) - cspec(2:end)));

在链接上给出的代码中。