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TSE
2011
144views more  TSE 2011»
14 years 4 months ago
Genetic Algorithms for Randomized Unit Testing
—Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing varies widely according to the settings of certain parameters, such...
James H. Andrews, Tim Menzies, Felix Chun Hang Li
PRL
2007
180views more  PRL 2007»
14 years 9 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
15 years 1 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
EPIA
2009
Springer
15 years 1 months ago
Semantic Image Search and Subset Selection for Classifier Training in Object Recognition
Abstract. Robots need to ground their external vocabulary and internal symbols in observations of the world. In recent works, this problem has been approached through combinations ...
Rui Pereira, Luís Seabra Lopes, Augusto Sil...
PRL
2006
130views more  PRL 2006»
14 years 9 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho