Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generating Counterfactual and Contrastive Explanations using SHAP   With the advent of GDPR, the domain of explainable AI and model
interpretability has gained added impetus. Methods to extract and communicate
visibility into decision-making models have become legal requirement. Two
specific types of explanations, contrastive and counterfactual have been
identified as suitable for human understanding. In this paper, we propose a
model agnostic method and its systemic implementation to generate these
explanations using shapely additive explanations (SHAP). We discuss a
generative pipeline to create contrastive explanations and use it to further to
generate counterfactual datapoints. This pipeline is tested and discussed on
the IRIS, Wine Quality & Mobile Features dataset. Analysis of the results
obtained follows.

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The categories of this paper are: plasm-ph
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The categories of this paper are: supr-con
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The categories of this paper are: cond-mat
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: quant-ph
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The categories of this paper are: physics
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The categories of this paper are: hep-th
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The categories of this paper are: q-bio
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The categories of this paper are: dg-ga
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The categories of this paper are: q-alg
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The categories of this paper are: hep-lat
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an