Unsupervised clustering applied to the optimization of a Case-based Reasoning system for the selection of optimal image explanation methods

The goal of this paper is to develop a cluster-based retrieval process to select the optimal explanation method for a given image and its corresponding classification by a neural network model. We propose the use of a density clustering method to organize a case base consisting of images labeled according to their optimal explanation method. This approach presents a prediction accuracy similar to a standard nearest-neighbor method, but significantly reducing the required retrieval time.

[1]  Mukund Sundararajan,et al.  Attribution in Scale and Space , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  David B. Leake,et al.  CBR Confidence as a Basis for Confidence in Black Box Systems , 2019, ICCBR.

[3]  Mark T. Keane,et al.  How Case-Based Reasoning Explains Neural Networks: A Theoretical Analysis of XAI Using Post-Hoc Explanation-by-Example from a Survey of ANN-CBR Twin-Systems , 2019, ICCBR.

[4]  Tolga Bolukbasi,et al.  XRAI: Better Attributions Through Regions , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[5]  Carlos Guestrin,et al.  Anchors: High-Precision Model-Agnostic Explanations , 2018, AAAI.

[6]  Cynthia Rudin,et al.  Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains its Predictions , 2017, AAAI.

[7]  Aurélien Géron,et al.  Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems , 2017 .

[8]  Ankur Taly,et al.  Axiomatic Attribution for Deep Networks , 2017, ICML.

[9]  Michael S. Bernstein,et al.  Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , 2016, International Journal of Computer Vision.

[10]  Carlos Guestrin,et al.  "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.

[11]  David McSherry,et al.  Introduction to the Special Issue on Explanation in Case-Based Reasoning , 2005, Artificial Intelligence Review.

[12]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[13]  Juan A. Recio-García,et al.  A Case-Based Approach for the Selection of Explanation Algorithms in Image Classification , 2021, ICCBR.

[14]  Ankur Taly,et al.  Exploring Principled Visualizations for Deep Network Attributions , 2019, IUI Workshops.