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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 12 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 12 months ago
Agent-based support for interactive search in conceptual software engineering design
While recent attempts to search a conceptual software engineering design search space with multi-objective evolutionary algorithms have yielded promising results, the practical ap...
Christopher L. Simons, Ian C. Parmee
GECCO
2008
Springer
175views Optimization» more  GECCO 2008»
13 years 12 months ago
Using differential evolution for symbolic regression and numerical constant creation
One problem that has plagued Genetic Programming (GP) and its derivatives is numerical constant creation. Given a mathematical formula expressed as a tree structure, the leaf node...
Brian M. Cerny, Peter C. Nelson, Chi Zhou
GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
13 years 12 months ago
Analysis of mammography reports using maximum variation sampling
A genetic algorithm (GA) was developed to implement a maximum variation sampling technique to derive a subset of data from a large dataset of unstructured mammography reports. It ...
Robert M. Patton, Barbara G. Beckerman, Thomas E. ...
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 12 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli