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/catalog_Orig/product_info.php?products_id=1688 for a more recent and comprehensive discussion.
- Publication:
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arXiv e-prints
- Pub Date:
- June 2021
- DOI:
- 10.48550/arXiv.2106.12417
- arXiv:
- arXiv:2106.12417
- Bibcode:
- 2021arXiv210612417H
- Keywords:
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- Computer Science - Machine Learning;
- Statistics - Machine Learning