2023
DOI: 10.1108/s1479-838720220000014006
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Garbage in, Garbage out: A Theory-Driven Approach to Improve Data Handling in Supervised Machine Learning

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Cited by 3 publications
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“…We are cautious of this approach's potential to threaten validity and generalizability by highlighting idiosyncratic linguistic relationships. Hence, we prune features in alignment with the existing literature prior to training the model (Hyde et al, 2023).…”
Section: Deceptionmentioning
confidence: 99%
“…We are cautious of this approach's potential to threaten validity and generalizability by highlighting idiosyncratic linguistic relationships. Hence, we prune features in alignment with the existing literature prior to training the model (Hyde et al, 2023).…”
Section: Deceptionmentioning
confidence: 99%