Titlebook: Recombineering; Methods and Protocol Christopher R. Reisch Book 2022 Springer Science+Business Media, LLC, part of Springer Nature 2022 CRI

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Katherine J. Wozniak,Lyle A. Simmons context in which explanation methods can be evaluated regarding their adequacy. The goal of this chapter is to bridge the gap between expert users and lay users. Different kinds of users are identified and their concerns revealed, relevant statements from the General Data Protection Regulation are

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Wei Hong,Jie Zhang,Guzhen Cui,Qian Zhou,Pixiang Wang,Yi Wang provide easy-to-interpret rationales for their behavior—so that passengers, insurance companies, law enforcement, developers etc., can understand what triggered a particular behavior. Here, we explore the use of visual explanations. These explanations take the form of real-time highlighted regions

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Zhiqiang Wen,Fenghui Qian,Jiao Zhang,Yu Jiang,Sheng Yangman-machine interactions. Expressing the rationale behind such a system’s output is an important aspect of human-machine interaction as AI continues to be prominent in general, everyday use-cases. In this paper, we introduce a novel framework integrating Grenander’s pattern theory structures to prod

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Justin M. Vento,Chase L. Beiselg to some of the attributes in our classification system, summarized in Tables ., ., . and .. The methods in each category are described and discussed. The categories are Decision Tree, Single Decision Tree, Single Altered Decision Tree, Multiple or Combined Decision Trees, Saliency Maps, Post-Hoc S

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help facilitate discussion of and research into this interdisciplinary field. We consider classification techniques used in past surveys and papers and attempt to unify terminology, describing 12 attributes that can be used to classify explainable/interpretable techniques: (i) Model-Agnostic or Mod

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