ROC curve for each fold in one plot

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ROC curve for each fold in one plot

R help mailing list-2
Hi all,

I have tried a 5 fold cross validation using caret package with random forest method on iris dataset as example. Then I need ROC curve for each fold:


  > set.seed(1)
  > train_control <- trainControl(method="cv", number=5,savePredictions = TRUE,classProbs = TRUE)
  > output <- train(Species~., data=iris, trControl=train_control, method="rf")
  > library(pROC)  
  > selectedIndices <- output$pred$Resample == "Fold1"
  > plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices])  > selectedIndices <- output$pred$Resample == "Fold2"  
  > plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices])
  > selectedIndices <- output$pred$Resample == "Fold3"
  > plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices])

and the same for Fold4 and Fold5,now how can I bring all the plots in one plot with labels for each fold?

Thanks for any help!
Elahe

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Re: ROC curve for each fold in one plot

PIKAL Petr
Hi

I did not see any response but what about

par(mfrow=c(2,2))

before plotting?

Cheers
Petr

> -----Original Message-----
> From: R-help [mailto:[hidden email]] On Behalf Of Elahe chalabi
> via R-help
> Sent: Monday, October 16, 2017 2:26 PM
> To: R-help Mailing List <[hidden email]>
> Subject: [R] ROC curve for each fold in one plot
>
> Hi all,
>
> I have tried a 5 fold cross validation using caret package with random forest
> method on iris dataset as example. Then I need ROC curve for each fold:
>
>
>   > set.seed(1)
>   > train_control <- trainControl(method="cv", number=5,savePredictions =
> TRUE,classProbs = TRUE)
>   > output <- train(Species~., data=iris, trControl=train_control, method="rf")
>   > library(pROC)
>   > selectedIndices <- output$pred$Resample == "Fold1"
>   >
> plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices
> ])  > selectedIndices <- output$pred$Resample == "Fold2"
>   >
> plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices
> ])
>   > selectedIndices <- output$pred$Resample == "Fold3"
>   >
> plot.roc(output$pred$obs[selectedIndices],output$pred$setosa[selectedIndices
> ])
>
> and the same for Fold4 and Fold5,now how can I bring all the plots in one plot
> with labels for each fold?
>
> Thanks for any help!
> Elahe
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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