similar to: ROC curve in R

HI, Dear R community, I want to know how to select the optimal decision threshold from the ROC curve? At what threshold will give the highest accuracy? Thanks! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

> x <- train[,c( 2:18, 20:21, 24, 27:31)] > y <- train$out > > svm.pr <- svm(x, y, probability = TRUE, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) > > pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], decision.values = TRUE, probability = TRUE) > attr(pred, "decision.values")[1:4,]

Hi, there. Suppose I already have sensitivities and specificities. What is the quick R-function to calculate AUC for the ROC plot? There seem to be many R functions to calculate AUC. Thanks. Yulei [[alternative HTML version deleted]]

Hi I'm new to stats and R, so can you please help me or guide me building ROC curve in an elaborate way with codes I loaded ROCR package, but I'm not sure how to use it. Requirement To build ROC curve using only PSA(variable) alone of the original cohort against the ROC of the Model of the original cohort. It would be really great if you could help me with this. Thanks

Hi, I understand for 1 d classifiers, you can use ROCR package. Is there a package you can plot ROC curve for 2d classifiers? One of my colleagues asked me about this. I have been quite puzzled, conceptually, how you can do the ROC curve for 2d classifiers. Can someone share his/her knowledge or experience? Thanks in advance. -- Waverley @ Palo Alto

Hi, I need to build ROC curve in R, can you please provide data steps / code or guide me through it. Thanks and Regards Rithesh M Mohan [[alternative HTML version deleted]]

Dear all, I want to measure the goodness of prediction of my linear model. That's why I was thinking about the area under roc curve. I'm trying the following, but I don't know how to avoid the error. Any help would be appreciated. library(ROCR) model.lm <- lm(log(outcome)~log(v1)+log(v2)+factor1) pred<-predict(model.lm) pred<-prediction(as.numeric(pred),

*Hi, *Does anyone know how can I show an *ROC curve for R-SVM*? I understand in R-SVM we are not optimizing over SVM cost parameter. Any example ROC for R-SVM code or guidance can be really useful. Thanks, Angel. [[alternative HTML version deleted]]

Hello, I would like to use the ROCR package to draw ROC curves and compute AUC values. However, in the specific context of my application, the true positive rates and false positive rates are already provided by some upstream method. Of course, I can draw a ROC plot with the following command : plot(x=FPrate, y=TPrate, "o", xlab="false positive rate", ylab="true

Hi everybody, I have a data set with a value and a status (positive or negative case) and I want make a ROC Analysis. So, with ROCR Package, I have got the ROC curve (True Positive Fraction [tpf] according 1-True Negative Fraction [1-tnf]). http://r.789695.n4.nabble.com/file/n4469203/01.png But, now I want a new graphic which show the sum of true positive fraction and true negative fraction

Hola! Tengo que hacer una curva ROC com unos datos que obtuve de hacer una macro de excel y aplicar unas reglas, y basicamente tengo que a partir de la variacion del tiempo y la velocidad del barco obtengo diferentes porcentajes de true positives (TP) y false positives (FP) y con eso deberia de construir una curva ROC. Dada mi ignorância en este tema, no se muy bien por donde empezar , estuve

Hello all, I am very new to R and i am facing two problems. First i didn't succeed changing the konsole language in english even after trying the line command set language='en'. I would like to plot ROC curves. I have a serie of 10 threshold tests that i do for 10 patients. The prediction for the patients is always the same but the status can change given to the considered threshold.

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

Hello, I have a classification tree. I want to obtain a ROC curve for this test. What is the easiest way to obtain one? -Anjali --------------------------------- [[alternative HTML version deleted]]

Hi, I don't really understand how ROCR works. Here's another example with a randomforest model: I have the training dataset(bank_training) and testing dataset(bank_testing) and I ran a randomForest as below: bankrf<-randomForest(y~., bank_training, mtry=4, ntree=2, keep.forest=TRUE,importance=TRUE) bankrf.pred<-predict(bankrf, bank_testing)

Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

Dear Guru's, Is there a package (R of course) with programs for diagnostics - roc, sens , spec, kappa etc? Best wishes Fredrik L

Hi, I am new here. I would like to compare the performance of the random forest model with support vector machine. Can anybody let me know how to generate a ROC curve for random forest model since there is no need to run the cross-validation. Thank you very much! TL _________________________________________________________________ [[replacing trailing spam]]

Dear all, I am looking for an R package that allows me to calculate and plot the confidence intervals for the roc curve using for example some bootstrapping. I tried "ROCR" who seems doing such work but i couldn't find the right option in it. Many thanks Bests Marc _________________________________________________________________ [[alternative HTML version deleted]]

Hi, I'm trying to set up a prediction software, now i testing the performance of my method, so i need to calculate a ROC curve, specially auc, cut-off, sens and spec, i just looking at ROCH package, but it's a mass for me, i'm not a math guy and I'm getting lost Could any of you recommend me an easy-to-use package to do this task? i just have a list of positive/negative samples