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» Adapting the Fitness Function in GP for Data Mining
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ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
14 years 2 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
GECCO
2008
Springer
250views Optimization» more  GECCO 2008»
13 years 8 months ago
Community detection in social networks with genetic algorithms
A new genetic algorithm to detect communities in social networks is presented. The algorithm uses a fitness function able to identify groups of nodes in the network having dense ...
Clara Pizzuti
ICDE
2006
IEEE
144views Database» more  ICDE 2006»
14 years 9 months ago
Approximately Processing Multi-granularity Aggregate Queries over Data Streams
Aggregate monitoring over data streams is attracting more and more attention in research community due to its broad potential applications. Existing methods suffer two problems, 1...
Shouke Qin, Weining Qian, Aoying Zhou
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
IJCAI
2007
13 years 9 months ago
A Subspace Kernel for Nonlinear Feature Extraction
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Mingrui Wu, Jason D. R. Farquhar