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» Phenomenal Data Mining: From Data to Phenomena
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SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
15 years 8 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 8 months ago
Clustering from Constraint Graphs
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Ari Freund, Dan Pelleg, Yossi Richter
KDD
2002
ACM
193views Data Mining» more  KDD 2002»
16 years 7 months ago
Query, analysis, and visualization of hierarchically structured data using Polaris
In the last several years, large OLAP databases have become common in a variety of applications such as corporate data warehouses and scientific computing. To support interactive ...
Chris Stolte, Diane Tang, Pat Hanrahan
AUSDM
2006
Springer
202views Data Mining» more  AUSDM 2006»
15 years 10 months ago
A Comparative Study of Classification Methods For Microarray Data Analysis
In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boostin...
Hong Hu, Jiuyong Li, Ashley W. Plank, Hua Wang, Gr...
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
15 years 8 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...