False perfection in machine prediction: Detecting and assessing circularity problems in machine learning
Abstract
This paper is an excerpt of an early version of Chapter 2 of the book "Validity, Reliability, and Significance. Empirical Methods for NLP and Data Science", by Stefan Riezler and Michael Hagmann, published in December 2021 by Morgan & Claypool. Please see the book's homepage at https://www.morganclaypoolpublishers.com/catalogOrig/productinfo.php?productsid=1688 for a more recent and comprehensive discussion.
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