File:ORES damaging false positive rates by newcomers and anons.png

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Summary

Description
English: ORES is a machine learning system for classifying edits to Wikipedia according to whether they are damaging or goodfaith. This plot shows that, for the 25 Wikis on which the ORES damaging models are deployed, and when the prediction threshold is chosen to maximize overall accuracy, that the model commonly has significant false positive rates for anonymous editors. Moreover, false positive rates for newcomers, while low, are greater than for other editors.
Date
Source Own work
Author Groceryheist

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Captions

This plot shows the false positve rates of ORES damaging models on edits by newcomers, anons, and other editors.

Items portrayed in this file

depicts

inception

23 April 2019

File history

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Date/TimeThumbnailDimensionsUserComment
current16:56, 2 May 2019Thumbnail for version as of 16:56, 2 May 20191,596 × 723 (115 KB)GroceryheistChange title
22:17, 25 April 2019Thumbnail for version as of 22:17, 25 April 20191,596 × 723 (115 KB)GroceryheistShow 4 facets for the different threshholds from Special:ORESModels
18:50, 24 April 2019Thumbnail for version as of 18:50, 24 April 20191,131 × 679 (39 KB)Groceryheistshow confidence intervals around points.
05:42, 24 April 2019Thumbnail for version as of 05:42, 24 April 20191,139 × 679 (27 KB)GroceryheistUser created page with UploadWizard

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