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» Discovering and ranking important rules
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GRC
2005
IEEE
13 years 10 months ago
Discovering and ranking important rules
— Decision rules generated from reducts can fully describe a data set. We introduce a new method of evaluating rules by taking advantage of rough sets theory. We consider rules g...
Jiye Li, Nick Cercone
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
13 years 11 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...
RSFDGRC
2005
Springer
110views Data Mining» more  RSFDGRC 2005»
13 years 10 months ago
A Rough Set Based Model to Rank the Importance of Association Rules
Abstract. Association rule algorithms often generate an excessive number of rules, many of which are not significant. It is difficult to determine which rules are more useful, int...
Jiye Li, Nick Cercone
ICMLA
2009
13 years 2 months ago
Discovering Characterization Rules from Rankings
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
ICAC
2009
IEEE
13 years 11 months ago
Ranking the importance of alerts for problem determination in large computer systems
The complexity of large computer systems has raised unprecedented challenges for system management. In practice, operators often collect large volume of monitoring data from system...
Guofei Jiang, Haifeng Chen, Kenji Yoshihira, Akhil...