Evolutionary decision tree induction with multi-interval discretization

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Saremi:2014:ICIS,

• author = "Mehrin Saremi and Farzin Yaghmaee",
• title = "Evolutionary decision tree induction with multi-interval discretization",
• booktitle = "Iranian Conference on Intelligent Systems (ICIS 2014)",
• year = "2014",
• month = "4-6 " # feb,
• address = "Bam",
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, decision tree induction, evolutionary algorithm, multi-interval discrimination",
• DOI = "doi:10.1109/IranianCIS.2014.6802543",
• abstract = "Decision trees are one of the widely used machine learning tools with their most important advantage being their comprehensible structure. Many classic algorithms (usually greedy top-down ones) have been developed for constructing decision trees, while in recent years evolutionary algorithms have found their application in this area. Discrimination is a technique which enables algorithms like decision trees to deal with continuous attributes as well as discrete attributes. We present an algorithm that combines the process of multi-interval discretisation with tree induction, and introduce especially designed genetic programming operators for this task. We compared our algorithm with a classic one, namely C4.5. The comparison results suggest that our method is capable of producing smaller trees.",
• notes = "Also known as \cite{6802543}",

}

Genetic Programming entries for Mehrin Saremi Farzin Yaghmaee

Citations