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[SoBigData] SoBigData Research Infrastructure (654024)
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  • Publication . Part of book or chapter of book . Conference object . Preprint . Article . 2020
    Open Access English
    Authors: 
    Riccardo Guidotti; Anna Monreale; Stan Matwin; Dino Pedreschi;
    Country: Italy
    Project: EC | PRO-RES (788352), EC | SoBigData (654024), EC | AI4EU (825619), EC | Track and Know (780754), NSERC

    We present an approach to explain the decisions of black box models for image classification. While using the black box to label images, our explanation method exploits the latent feature space learned through an adversarial autoencoder. The proposed method first generates exemplar images in the latent feature space and learns a decision tree classifier. Then, it selects and decodes exemplars respecting local decision rules. Finally, it visualizes them in a manner that shows to the user how the exemplars can be modified to either stay within their class, or to become counter-factuals by "morphing" into another class. Since we focus on black box decision systems for image classification, the explanation obtained from the exemplars also provides a saliency map highlighting the areas of the image that contribute to its classification, and areas of the image that push it into another class. We present the results of an experimental evaluation on three datasets and two black box models. Besides providing the most useful and interpretable explanations, we show that the proposed method outperforms existing explainers in terms of fidelity, relevance, coherence, and stability.

  • Authors: 
    Iain D. Stewart; Christopher Kennedy; Angelo Facchini; Renata Mele;
    Publisher: Informa UK Limited
    Project: EC | SoBigData (654024)

    Comprehensive frameworks for sustainable urban development have been advanced by many scholars and global institutions in recent years. These frameworks are broad and overlapping in nature, but eac...

Advanced search in
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[SoBigData] SoBigData Research Infrastructure (654024)
Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
2 Research products, page 1 of 1
  • Publication . Part of book or chapter of book . Conference object . Preprint . Article . 2020
    Open Access English
    Authors: 
    Riccardo Guidotti; Anna Monreale; Stan Matwin; Dino Pedreschi;
    Country: Italy
    Project: EC | PRO-RES (788352), EC | SoBigData (654024), EC | AI4EU (825619), EC | Track and Know (780754), NSERC

    We present an approach to explain the decisions of black box models for image classification. While using the black box to label images, our explanation method exploits the latent feature space learned through an adversarial autoencoder. The proposed method first generates exemplar images in the latent feature space and learns a decision tree classifier. Then, it selects and decodes exemplars respecting local decision rules. Finally, it visualizes them in a manner that shows to the user how the exemplars can be modified to either stay within their class, or to become counter-factuals by "morphing" into another class. Since we focus on black box decision systems for image classification, the explanation obtained from the exemplars also provides a saliency map highlighting the areas of the image that contribute to its classification, and areas of the image that push it into another class. We present the results of an experimental evaluation on three datasets and two black box models. Besides providing the most useful and interpretable explanations, we show that the proposed method outperforms existing explainers in terms of fidelity, relevance, coherence, and stability.

  • Authors: 
    Iain D. Stewart; Christopher Kennedy; Angelo Facchini; Renata Mele;
    Publisher: Informa UK Limited
    Project: EC | SoBigData (654024)

    Comprehensive frameworks for sustainable urban development have been advanced by many scholars and global institutions in recent years. These frameworks are broad and overlapping in nature, but eac...