Linked Questions

3
votes
1answer
2k views

draw roc curve on an example of 10 probability scores [duplicate]

I'm studying machine learning and find an example question on the book which really confused me. Q: A scoring classifier is evaluated on a test set of 10 examples resulting in the following ...
1
vote
0answers
792 views

Area under the ROC curve for continuous variable [duplicate]

I have the true output as the ratio between 0 and 1. I am trying predict the output using regression. I am supposed to find the area under the ROC curve between the prediction and true values. I am ...
0
votes
1answer
236 views

How are AUROC scores computed with just two vectors of actual and predicted values as input? [duplicate]

In the R package ModelMetrics, the auc score as shown in the documentation takes only two inputs; aucScore <- auc(actual=actuallabels, predicted=predictedlabels) where the inputs are pretty self ...
0
votes
0answers
113 views

ROC curve interpretation [duplicate]

In the context of binary classification how do you interpret ROC curve: more precisely: 1) Why the diagonal stand for a random classifier? [Edit] Let's imagine a random classifier: each time he ...
0
votes
0answers
63 views

How to plot ROC for LOOCV by hand based on output probabilities returned by SVM? [duplicate]

I want to plot ROC for Leave-one-out (LOO) cross-validation (CV). I have the decision values as well as probability values for each class from SVM classifier. I did see the answer to this post; ...
1
vote
0answers
59 views

Calculating AUC from continuous output [duplicate]

Calculating AUC for one threshold in the continuous output is simple: AUC = (TPR - FPR + 1) / 2; What if I want to calculate AUC for multiple thresholds in ...
0
votes
0answers
42 views

How to interpret ROC curve? [duplicate]

I am currently doing a classification problem for classifying the functional class and non-functional class of peptidase cleavage site. The data on non-functional class (negative class) is highly ...
225
votes
5answers
333k views

What does AUC stand for and what is it?

Searched high and low and have not been able to find out what AUC, as in related to prediction, stands for or means.
57
votes
1answer
56k views

Understanding ROC curve

I'm having trouble understanding the ROC curve. Is there any advantage / improvement in area under the ROC curve if I build different models from each unique subset of the training set and use it to ...
26
votes
3answers
25k views

Why is AUC higher for a classifier that is less accurate than for one that is more accurate?

I have two classifiers A: naive Bayesian network B: tree (singly-connected) Bayesian network In terms of accuracy and other measures, A performs comparatively worse than B. However, when I use the R ...
4
votes
2answers
3k views

How does AUC of ROC equal concordance probability? [duplicate]

If this answer on Quora is correct then I think I understand what concordance probability is. However, I also find that this answer on StackExchange provides the formula of concordance probability ...
3
votes
1answer
3k views

How to compare predictive power of survival models?

Frank Harrell describes the concordance (or Somer's D) as not being sensitive enough to compare multiple survival models for their diagnostic ability, and I've observed this in my own work with ...
5
votes
1answer
628 views

How is a ROCAUC=1.0 possible with imperfect accuracy? [duplicate]

I used sklearn to compute roc_auc_score for a dataset of 72 instances. The accuracy was at 97% (2 misclassifications), but the ROC AUC score was 1.0. How is this ...
1
vote
2answers
2k views

Meaning of model calibration

A previous post has discussed model discrimination very nicely. The post also briefly discussed calibration: "When evaluating a risk model, calibration is also very important. To examine this, ...
1
vote
1answer
1k views

What is the best way to calculate the AUC of a ROC curve?

I have a ROC curve for which I'd like to calculate the AUC. I'm getting different values using the trapezoidal and rank-based approaches. What I'm noticing is that the two values actually add to 1.0 ...
1
vote
2answers
584 views

AUC with incomplete ROC curve

I am doing an experiments where changing a parameter I am obtaining different number of FalsePositive, FalseNegative... and so on. I am using this parameter tuning as threshold tuning to obtain FPR ...
2
votes
2answers
532 views

How can I compare model fitting accuracy between Random Forest and Logistic regression models

I am conducting a classification problem. Usually AUC is used to check the effectiveness of a model when performing logistic regression model. However, if I fit the same data set by using Random ...
1
vote
1answer
564 views

Does AUC for multiple logistic regression make sense if prediction is not the goal?

Does it makes sense to calculate the AUC if I do not want to use my multiple logistic regression model for predictions? I only want to calculate some odds ratios and test if the variables in my model ...
1
vote
1answer
429 views

Are my data values too small for chi-squared for trend? If so what trend test can I do instead?

I'm doing a project about dilated kidneys, these can be arranged into mild, moderate and severe. There are 53 patients in total. I want to see if there is a trend in the severity of dilatation between ...
3
votes
1answer
325 views

Different visualization of AUC than ROC curve

There are multiple interpretations of area under ROC curve. (e.g What does AUC stand for and what is it? ). We also know that AUC is closely related to rank correlation. Are there also different ways ...
2
votes
2answers
107 views

Why does pROC roc work with non-probability predictions?

With the pROC package, I can do this: true <- c(1, 1, 1, 0) predicted <- c(0.5, 0.1, 0.6, 0.1) roc(true, predicted) which gives as expected: ...
1
vote
1answer
203 views

Distributed AUC calculation (or approximation)

I am trying to calculate the ROC AUC for a dataset where I can't fit predictions and labels in memory (10s/100s billions of samples). Is there a way to calculate the AUC in a distributed way or at ...
0
votes
1answer
55 views

Cox regression with lasso regression

Is it possible to perform lasso regression (glmnet with "cox") for variable selection and then conduct Cox regression using ...
2
votes
0answers
68 views

How to calculate the prediction score of a classificator?

I want to compare a given classification algorithm with others via the Area under the (ROC-)curve metric. Unfortunately this algorithm only outputs the values of the respective confusion matrix (TP, ...
0
votes
1answer
39 views

Correct conditional expectation via logistic regression but terrible AUC

Suppose you have a binary random variable $Y$, and several other random variables $X_1,...,X_p$. Your goal is to "predict $Y$ using $X_1,...,X_p$." So, you go ahead and fit logistic regression, which ...