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3 votes
1 answer
82 views

AUC - different interpretations

When browsing through literature about ROC - AUC, there seems to be a disparity. While some plot TPR and FPR, e.g. from Wikipedia: "The ROC curve is created by plotting the true positive rate (...
Stani Petrov's user avatar
5 votes
4 answers
5k views

Precision vs. specificity

I know that if we cannot afford to have false positive results, we should aim for high precision. My question is, how is precision different from specificity? Any examples?
MxML's user avatar
  • 71
3 votes
2 answers
108 views

Calculating "accuracy", "recall" etc. without classification

I have a set of models, that I'm comparing to each other with respect to prediction of a binary event. I'm using a few proper scores (Brier, log), but I also need accuracy, recall, sensitivity etc., ...
Accidental Statistician's user avatar
0 votes
0 answers
139 views

Can AUC increase while both sensitivity and specificity decrease?

Assume I am given two classifiers - A and B. Is it possible that the specificity and sensitivity obtained from using B will be higher than A, but the AUC of A will be higher than the AUC of B? Will ...
German_S's user avatar
2 votes
3 answers
1k views

Calculate the confidence interval of a balanced accuracy by taking the mean of the CIs of sensitivity and specificity?

Because sensitivity and specificity are typically estimated as binomial proportions (e.g. k = TP, n = TP+FN), we can use any of the methods used to estimate the confidence interval for binomial ...
incurious's user avatar
1 vote
1 answer
2k views

Is it possible for a model to have higher sensitivity/specificity but lower accuracy and AUC?

In the evaluation of classification models, I've found one model to have a higher accuracy and c-statistic (AUC) as compared to a second model. However, the second model has higher sensitivity, ...
a13a22's user avatar
  • 163
3 votes
0 answers
176 views

Assessing correlated predictions

Let's assume we have a prediction algorithm (if it helps, imagine it's using some boosted tree method) that does daily predictions for whether some event will happen to a unit (e.g. a machine that ...
Björn's user avatar
  • 35.2k
1 vote
0 answers
88 views

How to make specificity a stable evaluation metric?

ROC (including AUC) metrics are widely used for binary classification problems. AUC is usually selected to evaluate the model. However, some tasks may require high specificity with fixed sensitivity. ...
user2149631's user avatar
3 votes
1 answer
2k views

Sensitivity and specificity for non-binary outcome

I'm very new to machine learning (this is my second project and only the first significant one) and here's the problem I'm currently dealing with: I am evaluating the performance of a model that ...
user avatar
12 votes
3 answers
3k views

Classifier performance measure that combines sensitivity and specificity?

I have 2-classes labelled data on which I'm performing classification using multiple classifiers. And the datasets are well balanced. When assessing the classifiers' performance, I need to take into ...
Kalaji's user avatar
  • 355