Hi, I was trying to draw some ROC curves (prediction of case/control status), but seem to be getting a somewhat jagged plot. Can I do something that would 'smooth' it somewhat? Most roc curves seem to have many incremental changes (in x and y directions), but my plot only has 4 or 5 steps even though there are 22 data points. Should I be doing something differently?
How can I provide a URL/attachment for my plot? Not sure if I can provide reproducible code, but here is some pseudocode, let me know if you'd like more details: ##### ## generate roc and auc values ##### library(pROC) library(AUCRF) getROC <- function(d1train,d1test){ my_model <- AUCRF(formula= status ~ ., data=d1train, ranking='MDA',ntree=1000,pdel=0.05) my_opt_model <- my_model$RFopt my_probs <- predict(my_opt_model, d1test, type = 'prob') my_roc <- roc(d1test[,resp_col] ~ my_probs[,2]) aucval <- round(as.numeric(my_roc$auc),4) return(my_roc) } roc_1 <- getROC(dat1,dat1test) plot.roc(roc_1,col="brown3") > roc_1 Call: roc.formula(formula = d1test[, resp_col] ~ ibd_probs[, 2]) Data: ibd_probs[, 2] in 3 controls (d1test[, resp_col] 0) < 19 cases (d1test[, resp_col] 1). Area under the curve: 0.8596 > roc_1$sensitivities [1] 1.00000000 0.94736842 0.94736842 0.94736842 0.89473684 0.84210526 0.78947368 0.73684211 0.68421053 0.68421053 [11] 0.63157895 0.57894737 0.52631579 0.47368421 0.42105263 0.36842105 0.31578947 0.26315789 0.21052632 0.15789474 [21] 0.10526316 0.05263158 0.00000000 > roc_1$specificities [1] 0.0000000 0.0000000 0.3333333 0.6666667 0.6666667 0.6666667 0.6666667 0.6666667 0.6666667 1.0000000 1.0000000 [12] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 [23] 1.0000000 many thanks! [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org 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.