Explaining Inaccurate Predictions of Models through k-Nearest Neighbors

Zeki Bilgin, Murat Gunestas

2021

Abstract

Deep Learning (DL) models exhibit dramatic success in a wide variety of fields such as human-machine interaction, computer vision, speech recognition, etc. Yet, the widespread deployment of these models partly depends on earning trust in them. Understanding how DL models reach a decision can help to build trust on these systems. In this study, we present a method for explaining inaccurate predictions of DL models through post-hoc analysis of k-nearest neighbours. More specifically, we extract k-nearest neighbours from training samples for a given mispredicted test instance, and then feed them into the model as input to observe the model’s response which is used for post-hoc analysis in comparison with the original mispredicted test sample. We apply our method on two different datasets, i.e. IRIS and CIFAR10, to show its feasibility on concrete examples.

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Paper Citation


in Harvard Style

Bilgin Z. and Gunestas M. (2021). Explaining Inaccurate Predictions of Models through k-Nearest Neighbors.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 228-236. DOI: 10.5220/0010257902280236


in Bibtex Style

@conference{icaart21,
author={Zeki Bilgin and Murat Gunestas},
title={Explaining Inaccurate Predictions of Models through k-Nearest Neighbors},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={228-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010257902280236},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Explaining Inaccurate Predictions of Models through k-Nearest Neighbors
SN - 978-989-758-484-8
AU - Bilgin Z.
AU - Gunestas M.
PY - 2021
SP - 228
EP - 236
DO - 10.5220/0010257902280236