Paper Info
Title
The Effect Of Class Imbalance On Precision-Recall Curves
Abstract
In this note, I study how the precision of a binary classifier depends on the ratio r of positive to negative cases in the test set, as well as the classifier's true and false-positive rates. This relationship allows prediction of how the precision-recall curve will change with r, which seems not to be well known. It also allows prediction of how F-beta and the precision gain and recall gain measures of Flach and Kull (2015) vary with r.
Year
DOI
Venue
2021
10.1162/neco_a_01362
NEURAL COMPUTATION
DocType
Volume
Issue
Journal
33
4
ISSN
Citations 
PageRank 
0899-7667
1
0.41
References 
Authors
0
1
Name
Order
Citations
PageRank
Christopher K. I. Williams16807631.16