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Causality-based Explanation of Classification Outcomes
Published 15 Mar 2020 in cs.LG, cs.AI, cs.DB, and stat.ML | (2003.06868v2)
Abstract: We propose a simple definition of an explanation for the outcome of a classifier based on concepts from causality. We compare it with previously proposed notions of explanation, and study their complexity. We conduct an experimental evaluation with two real datasets from the financial domain.
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