15 questions linked to/from What is "baseline" in precision recall curve
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### Baseline for Precision-Related Metrics [duplicate]

When working with ROC-AUC as a metric for binary classification, one often considers a value of 0.5 as a baseline from a random classifier (i.e. a data-blind classifier that randomly classifies test ...
1 vote
795 views

### How to calculate the area under the precision-recall curve for the random classifier? [duplicate]

I know that the random classifier score in ROC AUC (Area under the curve) is always 0.5. My question is: how to calculate the Area under the precision-recall curve for the random classifier?
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### ROC vs precision-and-recall curves

I understand the formal differences between them, what I want to know is when it is more relevant to use one vs. the other. Do they always provide complementary insight about the performance of a ...
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### Area under the ROC curve or area under the PR curve for imbalanced data?

I have some doubts about which performance measure to use, area under the ROC curve (TPR as a function of FPR) or area under the precision-recall curve (precision as a function of recall). My data is ...
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### Calculating AUPR in R [closed]

It is easy to find a package calculating area under ROC, but is there a package that calculates the area under precision-recall curve?
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### What is AUC of PR-curve?

I understand that AUC under ROC curve is a classic evaluation measurement for classifiers (which is basically the accuracy). However, when data is imbalanced, PR will be alternative. So, what does the ...
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### What does it mean if the ROC AUC is high and the Average Precision is low?

I have a model that produces a high ROC AUC (0.90), but at the same time a low average precision (0.30). From what I've found, I think it might have to do something with imbalanced data (which the ...
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### PR AUC < 50% with ROC AUC > 90% - model good or bad?

I understand for highly imbalanced dataset - we need to look for precision-recall vs ROC AUC to better judge the model. My question is what is the range for PR AUC below which the model is bad? My ...
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### Precision and recall of a random classifier

My understanding of precision and recall tells me that there is a tradeoff between these two measures: you can improve one at the cost of the other. However, when I think of a random classifier (on a ...
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### Area Under the Precision Recall curve -similar interpretation to AUROC?

I am trying to interpret the AUCPR. Say I have the following Precision-Recall curve. Firstly: It ends at 0.38 on the y-axis because this particular plot has ...
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1 vote
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### What does a "flat region" of precision recall curve imply?

I am evaluating ML models (GBDTs) on various test sets using Precision-recall curve, and my goal is: within some precision range, get as high recall as possible. The precision-recall curves on most of ...
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### ROC AUC has $0.5$ as random performance. Does PR AUC have a similar notion?

In considering ROC AUC, there is a sense in which $0.5$ is the performance of a random model. Conveniently, this is true, no matter the data or the prior probability of class membership; the ROC AUC ...
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1 vote
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### What is the expected value of AUROCC for random predictions?

I was having a debate with co-workers today about the dependence of AUC on class imbalance, ie, the proportion of positive/negative instances in the response variable. It was suggested that when ...
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### What is "better-than-random" precision in clustering?

In Section 6.3.1 of the paper "No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems", it is mentioned that the algorithm proposed by the paper has ...
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1 vote