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» Unsupervised Clustering In Streaming Data
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NIPS
2008
14 years 11 months ago
Learning Taxonomies by Dependence Maximization
We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
Matthew B. Blaschko, Arthur Gretton
NIPS
2001
14 years 11 months ago
Agglomerative Multivariate Information Bottleneck
The Information bottleneck method is an unsupervised non-parametric data organization technique. Given a joint distribution
Noam Slonim, Nir Friedman, Naftali Tishby
PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
15 years 4 months ago
Data Mining for Intrusion Detection: From Outliers to True Intrusions
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...
Goverdhan Singh, Florent Masseglia, Céline ...
ICDE
2003
IEEE
148views Database» more  ICDE 2003»
15 years 11 months ago
Dynamic Clustering of Evolving Streams with a Single Pass
Stream data is common in many applications, e.g., stock quotes, merchandize sales record, system logs, etc.. It is of great importance to analyze these stream data. As one of the ...
Jiong Yang
FLAIRS
2004
14 years 11 months ago
Clustering Spatial Data in the Presence of Obstacles
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Xin Wang, Howard J. Hamilton