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An extension of the PMML standard to subspace clustering models
| Content Provider | ACM Digital Library |
|---|---|
| Author | Günnemann, Stephan Kremer, Hardy Seidl, Thomas |
| Abstract | In today's applications we face the challenge of analyzing databases with many attributes per object. For these high dimensional data it is known that traditional clustering algorithms fail to detect meaningful patterns: mining the full-space is futile. As a solution subspace clustering techniques were introduced. They analyze arbitrary subspace projections of the data to detect clustering structures. Recently, public available mining software integrates subspace clustering as a novel mining paradigm and sets the stage for its wide applicability. Though, a common standard to describe, exchange and process the subspace clustering results is still missing, which hinders the application in practice. In this work, we propose an extension of the PMML standard to describe mining models resulting from subspace clustering methods. Thus, we bridge the gap between the different tools and realize a common baseline the user can rely on. Our extension considers the various aspects subspace clustering models have to cope with, going beyond the ones of traditional clustering. We will integrate this novel PMML extension in the next version of our OpenSubspace toolkit. |
| Starting Page | 48 |
| Ending Page | 53 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450308373 |
| DOI | 10.1145/2023598.2023605 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-08-21 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Extension Clustering models Subspace Pmml standard |
| Content Type | Text |
| Resource Type | Article |
