- author = "Thi Hien Nguyen and Xuan Hoai Nguyen",
- title = "Learning in Stages: A Layered Learning Approach for Genetic Programming",
- booktitle = "IEEE International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF 2012)",
- year = "2012",
- month = "27 " # feb # "-1 " # mar,
- size = "4 pages",
- abstract = "In this paper, we propose a new layered learning approach for Genetic Programming (GP), called GPLL. Our new GPLL is an extension of the earlier work in [8] incorporating theoretically and experimentally founded components derived from progressive sampling (PS). This new version of GPLL is tested and compared with standard GP on three real-world problems. Tuned for computational efficiency, it is able to demonstrate very substantial reductions in computational cost for relatively small (and generally non-significant) reductions in generalisation accuracy. At the other extreme, computational costs are still substantially less than for GP, while generalisation accuracies are consistently slightly better.",
- keywords = "genetic algorithms, genetic programming, computational cost, computational efficiency, generalisation accuracy, layered learning approach, progressive sampling, real-world problems, learning (artificial intelligence)",
-
DOI = "
doi:10.1109/rivf.2012.6169838",
-
notes = "UCI Concrete compressive strength. StatLib Pollen.
StatLib census. Run time.
Also known as \cite{6169838}",
