Data+Shift: Supporting Visual Investigation of Data Distribution Shifts by Data Scientists
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Machine learning on data streams is increasingly more present in multiple domains. However, there is often data distribution shift that can lead machine learning models to make incorrect decisions. While there are automatic methods to detect when drift is happening, human analysis, often by data scientists, is essential to diagnose the causes of the problem and adjust the system. We propose Data+Shift, a visual analytics tool to support data scientists in the task of investigating the underlying factors of shift in data features in the context of fraud detection. Design requirements were derived from interviews with data scientists. Data+Shift is integrated with JupyterLab and can be used alongside other data science tools. We validated our approach with a think-aloud experiment where a data scientist used the tool for a fraud detection use case.
Description
CCS Concepts: Human-centered computing --> Visualization systems and tools; Computing methodologies --> Machine learning
@inproceedings{10.2312:evs.20221097,
booktitle = {EuroVis 2022 - Short Papers},
editor = {Agus, Marco and Aigner, Wolfgang and Hoellt, Thomas},
title = {{Data+Shift: Supporting Visual Investigation of Data Distribution Shifts by Data Scientists}},
author = {Palmeiro, João and Malveiro, Beatriz and Costa, Rita and Polido, David and Moreira, Ricardo and Bizarro, Pedro},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-184-7},
DOI = {10.2312/evs.20221097}
}