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» New probabilistic interest measures for association rules
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ISCI
2008
181views more  ISCI 2008»
14 years 11 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
ICSM
2002
IEEE
15 years 4 months ago
Measuring Software Functional Size: Towards an Effective Measurement of Complexity
Data manipulation, or algorithmic complexity, is not taken into account adequately in any of the most popular functional size measurement methods. In this paper, we recall some we...
De Tran-Cao, Ghislain Lévesque, Alain Abran
FLAIRS
2009
14 years 9 months ago
Mining Default Rules from Statistical Data
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
AMC
2008
88views more  AMC 2008»
14 years 12 months ago
Stopping rules for box-constrained stochastic global optimization
We present three new stopping rules for Multistart based methods. The first uses a device that enables the determination of the coverage of the bounded search domain. The second i...
Isaac E. Lagaris, Ioannis G. Tsoulos
SNAM
2011
246views more  SNAM 2011»
14 years 6 months ago
Market basket analysis with networks
The field of market basket analysis, the search for meaningful associations in customer purchase data, is one of the oldest areas of data mining. The typical solution involves th...
Troy Raeder, Nitesh V. Chawla