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Machine learning models/Proposed/Language-agnostic Wikipedia article quality model card - Meta

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This model card describes a model for predicting the quality of Wikipedia articles. It uses structural features extracted from the article and a simple set of weights and wiki-specific normalization critera to label Wikipedia articles in any language with a score between 0 and 1 (that can then be mapped to more recognized article quality classes such as Stubs). These scores are relative to a given language edition (not directly comparable across languages). The weights and feature selection were trained on editor asssessments from Arabic, English, and French Wikipedia. This model is a prototype and may still be substantially updated. Wikipedia articles range in quality from rich, well-illustrated, fully-referenced articles that fully cover their topic and are easy to read to single sentence stubs that define the topic of the article but do not offer much more information. It is very useful to be able to reliably distinguish between these extremes and the various stages of quality along

Machine learning models/Production/Language-agnostic Wikipedia article quality - Meta-Wiki Jump to content From Meta, a Wikimedia project coordination wiki < Machine learning models (Redirected from Machine learning models/Proposed/Language-agnostic Wikipedia article quality model card ) Model card This page is an on-wiki machine learning model card . A model card is a document about a machine learning model that seeks to answer basic questions about the model. Model Information Hub Model creator(s) Isaac Johnson Model owner(s) Isaac Johnson Model interface English Wikipedia example and Lift W

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