require(randomForest)

rf.pred<-predict(fit, valid, type="prob")
> rf.pred[1:20, ]
         0      1
16  0.0000 1.0000
23  0.3158 0.6842
43  0.3030 0.6970
52  0.0886 0.9114
55  0.1216 0.8784
75  0.0920 0.9080
82  0.4332 0.5668
120 0.2302 0.7698
128 0.1336 0.8664
147 0.4272 0.5728
148 0.0490 0.9510
153 0.0556 0.9444
161 0.0760 0.9240
162 0.4564 0.5436
172 0.5148 0.4852
176 0.1730 0.8270
215 0.0100 0.9900
222 0.0104 0.9896
255 0.1358 0.8642
267 0.1000 0.9000
> rf.pred<-predict(fit, valid, type="prob")
>
> rf.roc <- prediction(rf.pred[,2], valid[,32])
> rf.auc <- performance(rf.roc, 'tpr', 'fpr')
> plot(rf.auc)

Dear R community,

I am plot the ROC curve for randomforest result, I am not sure the above
code is right or not?

I just used the second column of the probabilities, the pr(outcome=1).

Can anyone give some comments?

****************************
someguys use the following codes to plot, but I can not use the treeresponse
commad in randomforest object directly.


# create model using random forest and bagging ensemble using conditional
inference trees
035    x.cf <- cforest(Class ~ ., data=BreastCancer[ind == 1,], control =
cforest_unbiased(mtry = ncol(BreastCancer)-2))
036    x.cf.pred <- predict(x.cf, newdata=BreastCancer[ind == 2,])
037    x.cf.prob <-  1- unlist(treeresponse(x.cf, BreastCancer[ind == 2,]),
use.names=F)[seq(1,nrow(BreastCancer[ind == 2,])*2,2)]
038









-- 
Sincerely,
Changbin
--

Changbin Du
DOE Joint Genome Institute
Bldg 400 Rm 457
2800 Mitchell Dr
Walnut Creet, CA 94598
Phone: 925-927-2856

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