GAP: Constructing and Selecting Features with Evolutionary Computation

Created by W.Langdon from gp-bibliography.bib Revision:1.8612

@InCollection{smith:2004:ECDM,

• author = "Matthew G. Smith and Larry Bull",
• title = "GAP: Constructing and Selecting Features with Evolutionary Computation",
• booktitle = "Evolutionary Computing in Data Mining",
• publisher = "Springer",
• year = "2004",
• editor = "Ashish Ghosh and Lakhmi C. Jain",
• volume = "163",
• series = "Studies in Fuzziness and Soft Computing",
• chapter = "3",
• pages = "41--56",
• keywords = "genetic algorithms, genetic programming, ADFs",
• ISBN = "3-540-22370-3",
• URL = "http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-175-22-33980376-0,00.html",
• DOI = "10.1007/3-540-32358-9_3",
• abstract = "The use of machine learning techniques to automatically analyze data for information is becoming increasingly widespread. In this chapter we examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified using the C4.5 decision tree learning algorithm. Genetic Programming is used to construct new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. A Genetic Algorithm is used to determine which set of features is the most predictive. Using ten well-known data sets we show that our approach, in comparison to C4.5 alone, provides marked improvement in a number of cases.",
• notes = "GA+GP system used to preprocess ten UCI datasets constructing and selecting new features before using C4.5",
• size = "16 pages",

}

Genetic Programming entries for Matthew G Smith Larry Bull

Citations