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20 April 2024 |
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Article overview
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A Model Explanation System: Latest Updates and Extensions | Ryan Turner
; | Date: |
30 Jun 2016 | Abstract: | We propose a general model explanation system (MES) for "explaining" the
output of black box classifiers. This paper describes extensions to Turner
(2015), which is referred to frequently in the text. We use the motivating
example of a classifier trained to detect fraud in a credit card transaction
history. The key aspect is that we provide explanations applicable to a single
prediction, rather than provide an interpretable set of parameters. We focus on
explaining positive predictions (alerts). However, the presented methodology is
symmetrically applicable to negative predictions. | Source: | arXiv, 1606.9517 | Services: | Forum | Review | PDF | Favorites |
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