id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
american_scientific_journal-12080	Kochetov Dmitrii	Testing Methods for Machine Learning Systems: From Data Validation to Model Evaluation	2025	13	.pdf	application/pdf	5367	202	27	The contribution is twofold: methodologically, by bringing diverse perturbation modes into a single experimental frame; and practically, by empirically demonstrating on one American Academic Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) - Volume 103, No 1, pp 330-342 332 controlled case how data perturbations jointly reshape accuracy, robustness, and fairness metrics — thereby clarifying the nuanced, practice-oriented accuracy–fairness trade-offs induced by post-processing interventions. Practical guidance on the selection and interpretation of fairness metrics is informed by [3], whose review of fairness measures underpins the joint use of Demographic Parity Gap and Equalized Odds Gap in the experimental battery.	cache/american_scientific_journal-12080.pdf	txt/american_scientific_journal-12080.txt