- author = "Farzad Noorian and Anthony M. {de Silva} and Philip H. W. Leong",
- title = "{gramEvol}: Grammatical Evolution in {R}",
- journal = "Journal of Statistical Software",
- year = "2016",
- volume = "71",
- number = "1",
- pages = "1--26",
- month = jul,
- keywords = "genetic algorithms, genetic programming, Grammatical Evolution",
- ISSN = "1548-7660",
-
URL = "
https://www.jstatsoft.org/article/view/v071i01/0",
-
URL = "https://www.jstatsoft.org/index.php/jss/article/view/v071i01",
-
URL = "
https://www.jstatsoft.org/index.php/jss/article/view/v071i01/v71i01.pdf",
-
DOI = "
doi:10.18637/jss.v071.i01",
-
code_url = "https://www.jstatsoft.org/index.php/jss/article/view/v071i01/3253",
-
code_url = "https://www.jstatsoft.org/index.php/jss/article/view/v071i01/3254",
-
code_url = "https://www.jstatsoft.org/index.php/jss/article/view/v071i01/3255",
- size = "26 pages",
- abstract = "We describe an R package which implements grammatical evolution (GE) for automatic program generation. By performing an unconstrained optimization over a population of R expressions generated via a user-defined grammar, programs which achieve a desired goal can be discovered. The package facilitates the coding and execution of GE programs, and supports parallel execution. In addition, three applications of GE in statistics and machine learning, including hyper-parameter optimization, classification and feature generation are studied",
-
notes = "Also known as \cite{JSSv071i01}
The University of Sydney",
