Effective Evaluation Measures for Subspace Clustering of Data Streams - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Marwan Hassani, Yunsu Kim, Seungjin Choi, Thomas Seidl. Effective Evaluation Measures for Subspace Clustering of Data Streams. In Jiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S. Tseng, editors, Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Gold Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papers. Volume 7867 of Lecture Notes in Computer Science, pages 342-353, Springer, 2013. [doi]

The following publications are possibly variants of this publication:

An effective evaluation measure for clustering on evolving data streamsHardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. kdd 2011: 868-876 [doi]

Subspace clustering of data streams: new algorithms and effective evaluation measuresMarwan Hassani, Yunsu Kim, Seungjin Choi, Thomas Seidl 0001. jiis, 45(3):319-335, 2015. [doi]

runs on WebDSL