Differential subgroups identify specific feature combinations where population differences in outcomes are most extreme, found via a new optimization objective and the DiffSub method.
2009.Causality(2 ed.)
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.LG 2verdicts
UNVERDICTED 2representative citing papers
The paper introduces the mutatis mutandis (MM) comparator as a causal alternative to the ceteris paribus (CP) comparator in discrimination testing, arguing that MM enables more realistic complainant-comparator pairs and creates new opportunities for machine learning methods.
citing papers explorer
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Differential Subgroup Discovery: Characterizing Where Two Populations Differ, and Why
Differential subgroups identify specific feature combinations where population differences in outcomes are most extreme, found via a new optimization objective and the DiffSub method.
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Mutatis Mutandis: Revisiting the Comparator in Discrimination Testing
The paper introduces the mutatis mutandis (MM) comparator as a causal alternative to the ceteris paribus (CP) comparator in discrimination testing, arguing that MM enables more realistic complainant-comparator pairs and creates new opportunities for machine learning methods.