similar to: ROC curves with ROCR

Hi there, I'm having some difficulty with the ROCR package. I've installed it fine, and the sample data works (ROCR.simple), however when I try to load my own data it complains that there is an error in prediction as the number of classes is not equal to 2. I read the data from a text file which contains one column of probabilities and one column of binary 0 and 1. I then put it into a

Is it possible to use ROCR to plot a simple recall at p plot? I.e., a plot where the x-axis is the position into the ranked test set, and the y-axis is the recall, so you can see what's the recall in the top 10% of the ranked results. I searched through the performance() manual but found nothing. (Not a cutoff-vs-recall graph, since the cutoff is the probability estimate returned by the

Hello, I'd need to compute the calibration error of posterior class probabilities p(y|x) estimated by using rpart as classification tree. Namely, I train rpart on a dataset D and then use predict(... type="prob") to estimate p(y|x). I've found the possibility to do that in the ROCR package, but I cannot find a link to a paper/book which explains the details of the

I meet lots of problem when installing the package ROCR, do you have meet such problems? 1, biocLite("ROCR") 2, biocLite("gplots") 3, biocLite("Rgraphviz") 4, sudo apt-get install graphviz oh, no, unlimited question, what's wrong with R in ROCR or gplots or et al Error : object ‘nobs’ is not exported by 'namespace:gdata' installation of package

When I try to install the ROCR package (which requires gplots) on Ubuntu 9.10 (Xubuntu Karmic Koala) 64-bit on R version 2.9.2 (2009-08-24), it eats up all my RAM (2GB) and swap (4GB) and keeps allocating more memory until Linux's out of memory (OOM) killer kills the perl process. This problem is special to Ubuntu because I can install other packages (such as party) on this Ubuntu system, and

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing

Dear useRs, an update of the ROCR package is available on CRAN. ROCR helps in evaluating the performance of scoring classifiers using ROC graphs, precision/recall plots, lift charts and many other performance metrics. For further information check http://rocr.bioinf.mpi-sb.mpg.de and http://bioinformatics.oxfordjournals.org/cgi/reprint/21/20/3940 NEWS: - added an optional parameter

Dear useRs, an update of the ROCR package is available on CRAN. ROCR helps in evaluating the performance of scoring classifiers using ROC graphs, precision/recall plots, lift charts and many other performance metrics. For further information check http://rocr.bioinf.mpi-sb.mpg.de and http://bioinformatics.oxfordjournals.org/cgi/reprint/21/20/3940 NEWS: - added an optional parameter

Hi, I am using logistic regression to classify a binary psychometric data. using glm() and then predict.glm() i got the predicted odds ratio of the testing data. Next i am going to plot ROC curve for the analysis of my study. Now what i will do: 1. first select a cut-off (say 0.4) and classify the output of predict.glm() into {0,1} segment and then use it to draw ROC curve using ROCR package

Dear R-helper, I am working with ROCR of Tobias Sing et. al. to compare the performances of logistic and nnet models on a binary response. I had the performance plots, but I have problem finding out other performance statistics (eg. MSE/ASE, AUC). Any help on this? Thanks Ilham [[alternative HTML version deleted]]

Dear list, I am trying to build a cox model and then perform ROC analysis in order to retrieve some genes that are correlated with breast cancer. When I calculate the hazard score taking into account different numbers of genes and their coefficients ( I am trying to find the pest predictor number of genes), I retrieve from around 1 values (for few genes included ) to size of e+80 values (for many

Dear List,   I am new to ROC analysis and the package ROCR. I want to compute the confidence intervals of sensitivity and specificity for a given cutoff value. I have used the following to calculate sensitivity and specificity:   data(ROCR.simple) pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels)   se.sp <- function (cutoff, performance) {     sens <-

Hello, I've come across a strange error... Here is what happens: model <- svm(traindata,trainlabels, type="C-classification", kernel="radial", cost=10, class.weights=c("win"=3,"lose"=1), scale=FALSE, probability = TRUE) predictions <- predict(model, traindata) pred <- prediction(predictions, trainlabels) This returns an error: Error in

Dear R-philes, I am having some trouble averaging across multiple runs of a classifier in an ROC Curve. I am using the ROCR package and the plot() method. First, I initialize a list with two elements where each element is a list of predictions and labels: vowel.ROC <- list(predictions=list(), labels=list()) For every run of the classifier, I append the scores and labels to their

Hello all, I have two problems with the ROCR package. First Problem: the add=TRUE option does not work for plotting performance objects The following code is taken from the reference manual (example for ROCR.hiv, page2) data(ROCR.hiv) attach(ROCR.hiv) pred.svm <- prediction(hiv.svm$predictions, hiv.svm$labels) perf.svm <- performance(pred.svm, 'tpr', 'fpr') pred.nn <-

Dear R team I have a problem with the installation of the RCOR package; any time I try to install it I get the error message: Error: package 'ROCR' was built before R 2.10.0: please re-install it. What can I do to solve this problem? Thank you Kind regards Dr. Matteo Pettinari Senior Assistant Cardiale Heelkunde matteo.pettinari@uzleuven.be<mailto:matteo.pettinari@uzleuven.be>

Dear experts, I am looking for a package that does logistic regression with corssvalidation and gives me the probabilites of all the corssvalidations so that I can plot them in ROCR. Would also like to know if the corssvalidate model would give me a summary coefficient for the intercept and my to predictors. Thank you. Best regards, Jon Toledo, MD Postdoctoral fellow University of Pennsylvania

I'm trying to use ROCR to create a simple cutoff vs recall plot (recall at p) on the example ROCR.simple dataset: library(ROCR) data(ROCR.simple) pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels) perf <- performance(pred, "rec") plot(perf) But R crashes on me on the last line. I'm using R 2.14.1, ROCR 1.0-4. ?Any ideas? Thanks in advance. -- Yang Zhang

Dear R-help and ROCR developers (Tobias Sing and Oliver Sander) - I think my first question is generic and could apply to many methods, which is why I'm directing this initially to R-help as well as Tobias and Oliver. Question 1. The plot function in ROCR will average your cross validation data if asked. I'd like to use that averaged data to find a "best" cutoff but I