NIST · ИТ · 6224ed883f166ecfc59c
Explainable Validation and Feature Reduction in Machine Learning
Although there are many available approaches for designing machine learning models and experiments, not all of these approaches are explainable or interpretable. Combination frequency differencing (CFD) provides information on the relationship between
NIST · ИТОфициальный источник · 2026-05-17
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"title_en": "Explainable Validation and Feature Reduction in Machine Learning",
"designation": "",
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"date": "2026-05-17",
"date_original": "May 17, 2026",
"url": "https://www.nist.gov/publications/explainable-validation-and-feature-reduction-machine-learning",
"source": "NIST Publications",
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"authors_en": "Fenrir Badorf, Francis Durso , Callie Walker, Megan Olsen, M S Raunak , D. Richard Kuhn",
"abstract_excerpt_en": "Although there are many available approaches for designing machine learning models and experiments, not all of these approaches are explainable or interpretable. Combination frequency differencing (CFD) provides information on the relationship between",
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"title_en": "Explainable Validation and Feature Reduction in Machine Learning",
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"authors_en": "Fenrir Badorf, Francis Durso , Callie Walker, Megan Olsen, M S Raunak , D. Richard Kuhn",
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