IEEE BigData 2021 Cup: Soft Sensing at Scale is a data mining competition organized by Seagate Technology, in association with the IEEE BigData 2021 conference. The scope of this challenge is to tackle the task of classifying soft sensing data with machine learning techniques. In this paper we go into the details of the challenge and describe the data set provided to participants. We define the metrics of interest, baseline models, and describe approaches we found meaningful which may be a good starting point for further analysis. We discuss the results obtained with our approaches and give insights on what potential challenges participants may run into. Students, researchers, and anyone interested in working on a major industrial problem are welcome to participate in the challenge!
Cite
@article{arxiv.2109.03181,
title = {IEEE BigData 2021 Cup: Soft Sensing at Scale},
author = {Sergei Petrov and Chao Zhang and Jaswanth Yella and Yu Huang and Xiaoye Qian and Sthitie Bom},
journal= {arXiv preprint arXiv:2109.03181},
year = {2022}
}
Comments
4 pages, 4 figures, for IEEE Big Data Cup challenge 2021