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DAGSTUHL
2004
13 years 9 months ago
Knowledge-Based Sampling for Subgroup Discovery
Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The search is guided by a so-called utility function...
Martin Scholz
KDD
1997
ACM
154views Data Mining» more  KDD 1997»
13 years 11 months ago
Autonomous Discovery of Reliable Exception Rules
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Einoshin Suzuki
ICDM
2007
IEEE
138views Data Mining» more  ICDM 2007»
13 years 11 months ago
Preserving Privacy through Data Generation
Many databases will not or can not be disclosed without strong guarantees that no sensitive information can be extracted. To address this concern several data perturbation techniq...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
14 years 8 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li
PKDD
2005
Springer
109views Data Mining» more  PKDD 2005»
14 years 1 months ago
An Imbalanced Data Rule Learner
Imbalanced data learning has recently begun to receive much attention from research and industrial communities as traditional machine learners no longer give satisfactory results. ...
Canh Hao Nguyen, Tu Bao Ho