similar to: Como construir una curva ROC

Hola, Marta, Por lo que he podido ver tus datos ya tienen calculados las tasas de verdaderos y falsos positivos (TPR y FPR). También parece que los tienes ordenados por la variable FishSpeed y supongo que también por las que parecen marcas de tiempo. No necesitas ROCR porque con un simple plot te sale algo parecido a una curva. Eso sí, veo que son medidas repetidas en el tiempo para cada valor de

Hi, I am quite new to R and I have two questions regarding ROCR. 1. I have tried to understand how to extract area-under-curve value by looking at the ROCR document and googling. Still I am not sure if I am doing the right thing. Here is my code, is "auc1" the auc value? " pred1 <- prediction(resp1,label1) perf1 <- performance(pred1,"tpr","fpr") plot(

Buenas noches. Quisiera saber si existe una libreria o función que me calcule el área bajo la curva de dos vectores de números. Ademas esta debe tener en cuenta si existen datos faltantes o NaN. Por ejemplo calcular el área bajo la curva del vector en el eje x: x<- c(1,2,3,4,5,6,7,8,9,10) y el vector en el eje y: y<-c(0,2,15,30,50,NaN,NaN,10,2,1) Muchas gracias. -- *Wilmer

I am trying to use package ROCR to analyze classification accuracy, unfortunately there are some problems right at the beginning. Question 1) When I try to run demo I am getting the following error message > library(ROCR) > demo(ROCR) > if(dev.cur() <= 1) .... [TRUNCATED] Error in get(getOption("device")) : wrong first argument When I issue the command > dev.cur() it

Estimado Wilmer Contreras Sepulveda Me parece buena la sugerencia de Jorge, hay muchas formas, yo aparte de la sugerencia que le hicieron le agrego otras dos, en cualquier buscador las palabras claves son R AUC, y el artículo https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/ , lógicamente aparecerán tantas alternativas que puede llegar a confundirse respecto a cuál es

All, I'm trying again with a slightly more generic version of my first question. I can extract the plotted values from hist(), boxplot(), and even plot.randomForest(). Observe: # get some data dat <- rnorm(100) # grab histogram data hdat <- hist(dat) hdat #provides details of the hist output #grab boxplot data bdat <- boxplot(dat) bdat #provides details of the boxplot

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

Hi, I have an object from the prediction function from the ROCR package and I would like to extract one of the slots from the object, for example the cutoffs slot. However the usual techniques ($, [["name"]]) of subsetting don't work. How can I assess the lists in the slots? Here is an example of what I am working with: library(ROCR) data(ROCR.simple) pred <-

I have tried installing the package (ROCR) with this command: Install.packages(ROCR) And with this command on the command line R CMD INSTALL ROCR_1.0-4.tar.gz But both times I get exactly the same error shown below, I don't understand what is wrong, is this an error in the package code? Thank you Philip probinson@bioinform08:/tmp/RtmpO0rFbx/downloaded_packages$ R CMD

AF_E PS_E 90.838 2.206 83.139 1.751 134.272 3.710 84.043 2.076 105.184 2.788 157.249 3.783 50.280 1.027 96.973 2.355 123.582 3.398 60.417 1.236 123.501 3.315 90.128 1.566 193.783 5.167 116.036 2.994 100.289 2.216 56.943 1.106 102.272 2.692 145.579 3.810 53.105 1.202 127.212 3.061 102.838 2.383 126.352 2.723 13.661 0.190 164.352 4.870 159.945 4.160 54.382 0.884 128.253 3.598 181.208 4.767 145.118

Dear all, I was wondering if someone can help me. I am learning SVM for classification in my research with kernlab package. I want to know about classification performance using Area Under Curve (AUC). I know ROCR package can do this job but I found all example in ROCR package have include prediction, for example, ROCR.hiv {ROCR}. My problem is how to produce prediction in SVM and to find

I use ROCR to plot multiple runs' performance. Using the sample code as example: # plot ROC curves for several cross-validation runs (dotted # in grey), overlaid by the vertical average curve and boxplots # showing the vertical spread around the average. data(ROCR.xval) pred <- prediction(ROCR.xval$predictions, ROCR.xval$labels) perf <- performance(pred,"tpr","fpr")

Packages pROC and ROCR both calculate/approximate the Area Under (Receiver Operator) Curve. However the results are different. I am computing a new variable as a predictor for a label. The new variable is a (non-linear) function of a set of input values, and I'm checking how different parameter settings contribute to prediction. All my settings are predictive, but some are better. The AUC i

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 <-

Buenos dias R-help-es, Estoy interesado en estimar una curva dosis-respuesta para un conjunto de datos y para ello, estoy utilizando la libreria "drm". Hasta ahi todo bien. Me gustaria automatizar algunas cosas y el primer paso para ello es la estimacion del modelo. Si la estimacion funciona, todo lo demas funciona; de lo contrario, todo fallara. Tengo algunas lineas que mitigan un

If we use the ROCR package to find the accuracy of a classifier pred <- prediction(svm.pred, testset[,2]) perf.acc <- performance(pred,"acc") Do we?find the maximum accuracy?as follows?(is there a simplier way?): > max(perf.acc at x.values[[1]]) Then to find the cutoff point that maximizes the accuracy?do we do the following?(is there a simpler way): > cutoff.list <-

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

Hi everybody, I am having a problem building a ROC curve with my data using the ROCR package. I have 10 lists of proteins such as attached (proteinlist.xls). each of the lists was calculated with a different p-value. The goal is to find the optimal p-value for the highest number of true positives as well as lowaest number of false positives. As far as I understood the explanations from the

Hola a todos, Estoy intentando utilizar este script para hacer un plot con valores x ,y,z; representando los valores TP(y) y FP(x) y en funcion de la velocidad que seria el factor alpha. Y me da este en el ultimo punto de hacer el plot, alguien sabe que significa? library(ROCR) data(ROCR.simple) pred <- prediction( ROCR.simple$predictions, ROCR.simple$labels ) perf <- performance( pred,

Hola, quiero ajustar una curva sinoidal de la forma "f(x)=k/( 1+(c/log(x))^n)" mediante la función 'nls' pero me da error el siguiente código: >datos<-read.table(file="datos.csv", header=TRUE,sep=";",dec=",") >library(nls) >fit <- nls(y ~ k/(1+(c/log(x))^n), datos, start = list (k=100 , c =5*10^(-6), n=1)) Error en