Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
The XCS Learning Classifier System has traditionally used roulette wheel selection within its genetic algorithm component. Recently, tournament selection has been suggested as prov...
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...
Traditional channel quantization based methods for encryption key generation usually suffer from the quantization error which may decrease the key agreement ratio between authoriz...