IEEE BigData 2021 Cup: Soft Sensing at Scale

TL;DR

This paper details the IEEE BigData 2021 Cup focused on classifying soft sensing data using machine learning, providing datasets, metrics, baseline models, and insights to guide participants in tackling a major industrial classification challenge.

Contribution

It introduces a comprehensive dataset, evaluation metrics, baseline models, and analysis methods for the challenge of soft sensing data classification at scale.

Findings

Baseline models established for soft sensing classification.

Insights into potential challenges in industrial data classification.

Guidelines for further analysis and model improvement.

Abstract

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!