- author = "Jose Maria Luna and Jose Raul Romero and Cristobal Romero and Sebastian Ventura",
- title = "On the Use of Genetic Programming for Mining Comprehensible Rules in Subgroup Discovery",
- journal = "IEEE Transactions on Cybernetics",
- year = "2014",
- volume = "44",
- number = "12",
- pages = "2329--2341",
- month = dec,
- keywords = "genetic algorithms, genetic programming, Data mining (DM), grammar-guided genetic programming (G3P), subgroup discovery (SD)",
- ISSN = "2168-2267",
-
DOI = "
doi:10.1109/TCYB.2014.2306819",
- size = "13 pages",
- abstract = "This paper proposes a novel grammar-guided genetic programming algorithm for subgroup discovery. This algorithm, called comprehensible grammar-based algorithm for subgroup discovery (CGBA-SD), combines the requirements of discovering comprehensible rules with the ability to mine expressive and flexible solutions owing to the use of a context-free grammar. Each rule is represented as a derivation tree that shows a solution described using the language denoted by the grammar. The algorithm includes mechanisms to adapt the diversity of the population by self-adapting the probabilities of recombination and mutation. We compare the approach with existing evolutionary and classic subgroup discovery algorithms. CGBA-SD appears to be a very promising algorithm that discovers comprehensible subgroups and behaves better than other algorithms as measures by complexity, interest, and precision indicate. The results obtained were validated by means of a series of nonparametric tests.",
-
notes = "UCI
Also known as \cite{6756991}",
