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DAWAK
2006
Springer
13 years 11 months ago
Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation
Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Ahmed HajYasien, Vladimir Estivill-Castro
JMLR
2010
118views more  JMLR 2010»
13 years 2 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
WSC
2007
13 years 9 months ago
New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results
Statistical selection procedures can identify the best of a finite set of alternatives, where “best” is defined in terms of the unknown expected value of each alternative’...
Stephen E. Chick, Jürgen Branke, Christian Sc...
TON
2008
155views more  TON 2008»
13 years 7 months ago
A comparative analysis of server selection in content replication networks
Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical i...
Tao Wu, David Starobinski
HIS
2007
13 years 9 months ago
Active Selection of Training Examples for Meta-Learning
Meta-Learning has been used to relate the performance of algorithms and the features of the problems being tackled. The knowledge in Meta-Learning is acquired from a set of meta-e...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...