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Rectifying Mono-Label Boolean Classifiers

arXiv 2206.08758 ↗First posted 17 Jun 2022cs.AIcited by 0

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Abstract (arXiv)

We elaborate on the notion of rectification of a Boolean classifier Sigma. Given Sigma and some background knowledge T, postulates characterizing the way Sigma must be changed into a new classifier Sigma star T that complies with T have already been presented. We focus here on the specific case of mono-label Boolean classifiers, i.e., there is a single target concept and any instance is classified either as positive (an element of the concept), or as negative (an element of the complementary concept). In this specific case, our main contribution is twofold: (1) we show that there is a unique rectification operator star satisfying the postulates, and (2) when Sigma and T are Boolean circuits, we show how a classification circuit equivalent to Sigma star T can be computed in time linear in the size of Sigma and T; when Sigma and T are decision trees, a decision tree equivalent to Sigma star T can be computed in time polynomial in the size of Sigma and T.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 35 references that are in the map. First posted on arXiv 17 Jun 2022.

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References · 9

  1. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  2. 2018A Survey Of Methods For Explaining Black Box Modelscited by 970
  3. 2021Interpretable Machine Learning: Fundamental Principles and 10 Grand Challengescited by 364
  4. 2020On the Tractability of SHAP Explanationscited by 92
  5. 2020Model Interpretability through the Lens of Computational Complexitycited by 75
  6. 2021On the Computational Intelligibility of Boolean Classifierscited by 40
  7. 2021On Efficiently Explaining Graph-Based Classifierscited by 37
  8. 2021Trading Complexity for Sparsity in Random Forest Explanationscited by 32
  9. 2020On Relating 'Why?' and 'Why Not?' Explanationscited by 15

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