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» Data mining for discrimination discovery
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SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
14 years 4 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 8 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
KDD
2008
ACM
264views Data Mining» more  KDD 2008»
14 years 8 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
14 years 8 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu