I have tried 2 methods to plot ROC curve and get AUC for each ROC curve. Method 1 - The first method is simple but I don't know how to plot multiple ROC curves together. I am simply using roc.cur...

I am plotting ROCs and measuring partial AUC as a metric of ecological niche model quality. As I am working in R, I am using the ROCR and the pROC packages. I'll settle on one to use, but for now, ...

I have some machine learning results that I am trying to make sense of. The task is to predict/label "Irish" vs. "non-Irish". Python 2.7's output: 1= ir 0= non-ir Class count: 0 4090942 1 940852 N...

I am training ML logistic classifier to classify two classes using python scikit-learn. They are in an extremely imbalanced data (about 14300:1). I'm getting almost 100% accuracy and ROC-AUC, but 0...

I met a problem of 3-class ROC analysis in R and obtained a very annoying result (see here). Now I try to use a different way to solve it. The data is iris and the classifier is multinomial logisti...

I have an understanding problem by using the roc libraries. I want to plot a roc curve with a python http://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html I am writi...

Is it possible to plot the roc curve for diffrent classifiers in the same plot using the ROCR package? I've tried: >plot(perf.neuralNet, colorize=TRUE) >lines(perf.randomForest) But I get: ...

I am performing logistic regression using this page. My code is as below. mydata <- read.csv("http://www.ats.ucla.edu/stat/data/binary.csv") mylogit <- glm(admit ~ gre, data = mydata, family...

I have some machine learning results that I don't quite understand. I am using python sciki-learn, with 2+ million data of about 14 features. The classification of 'ab' looks pretty bad on the prec...

I want to create a roc object by using the function 'roc' of pROC package in R, and plot the roc object. However, I am uncertain what the 'direction' argument does. the median predictor values of m...

Correct me if I'm wrong: the "thresholds" returned by scikit-learn's roc_curve should be an array of numbers that are in [0,1]. However, it sometimes gives me an array with the first number close t...

How to plot a ROC curve using ROCR package in r, with only a classification contingency table? I have a contingency table where the true positive, false positive.. etc. all the rated can be comput...

I'm tying to calculate the AUC using auc(roc(predictions, labels)), where labels is a numeric vector of 1 (x15) and 0 (x500), and predictions is a numeric vector with probabilities derived from a g...

I would like to get the optimal cut off point of the ROC in logistic regression as a number and not as two crossing curves. Using the code below I can get the plot that will show the optimal point ...

The sklearn roc_curve docstring states: "y_score : array, shape = [n_samples] Target scores, can either be probability estimates of the positive class, confidence values, or binary decisions." In...

I am using sklearn v 0.13.1 svm in order to try and solve a binary classification problem. I use kfold cross validation and compute the area under the roc curve (roc_auc) to test the quality of my ...

When I use multiclass.roc function in R (pROC package), for instance, I trained a data set by random forest, here is my code: # randomForest & pROC packages should be installed: # install.pack...

I write a classifier (Gaussian Mixture Model) to classify five human actions. For every observation the classifier compute the posterior probability to belong to a cluster. I want to valutate the ...

I have a binary classifier, which classifies an input X as class zero if its predicted value is below some threshold (say T), and one otherwise. I have all predicted and actual values for every inp...

I'm trying to plot ROC curve of a random forest classification. Plotting works, but I think I'm plotting the wrong data since the resulting plot only has one point (the accuracy). This is the code...

I'm trying to classify a data set containing two classes using different classifiers (LDA, SVM, KNN) and would like to compare their performance. I've made ROC curves for the LDA by modifying the p...

I am building receiver operating characteristic (ROC) curves to evaluate classifiers using the area under the curve (AUC) (more details on that at end of post). Unfortunately, points on the curve o...

I am using randomForest package in R platform for classification task. rf_object<-randomForest(data_matrix, label_factor, cutoff=c(k,1-k)) where k ranges from 0.1 to 0.9. pred <- predict...