Abstract
Clustering is an important technique in data analysis which can reveal hidden patterns and unknown relationships in the data. A common problem in clustering is the proper choice of parameter settings. To tackle this, automated algorithm configuration is available which can automatically find the best parameter settings. In practice, however, many of our today’s data sources are data streams due to the widespread deployment of sensors, the internet-of-things or (social) media. Stream clustering aims to tackle this challenge by identifying, tracking and updating clusters over time. Unfortunately, none of the existing approaches for automated algorithm configuration are directly applicable to the streaming scenario. In this paper, we explore the possibility of automated algorithm configuration for stream clustering algorithms using an ensemble of different configurations. In first experiments, we demonstrate that our approach is able to automatically find superior configurations and refine them over time.
Original language | English |
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Title of host publication | Machine Learning and Knowledge Discovery in Databases |
Subtitle of host publication | International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I |
Publisher | Springer |
Pages | 137-143 |
Number of pages | 7 |
ISBN (Electronic) | 978-3-030-43823-4 |
ISBN (Print) | 978-3-030-43822-7 |
DOIs | |
Publication status | Published - 2020 |
Externally published | Yes |
Event | European Conference on Machine Learning and Knowledge Discovery in Databases, ECML-PKDD 2019 - Hubland campus University of Würzburg, Würzburg, Germany Duration: 16 Sep 2019 → 20 Sep 2019 https://ecmlpkdd2019.org/ |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1167 |
Conference
Conference | European Conference on Machine Learning and Knowledge Discovery in Databases, ECML-PKDD 2019 |
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Abbreviated title | ECML-PKDD 2019 |
Country/Territory | Germany |
City | Würzburg |
Period | 16/09/19 → 20/09/19 |
Internet address |