Genetic transfer learning

摘要

Transfer learning is a method which aims to improve “related” tasks performance. Transfer learning tries to use information gained from related tasks solutions to improve performance of learning strategy. Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the training and testing problems have different distributions or features (Pan, Kwok, & Yang, 2008). In this paper we have used transfer learning to improve performance of genetic algorithms.