Multi Objective Genetic Programming for Feature Construction in Classification Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{conf/lion/CastelliMV11,

• author = "Mauro Castelli and Luca Manzoni and Leonardo Vanneschi",
• title = "Multi Objective Genetic Programming for Feature Construction in Classification Problems",
• booktitle = "5th International Conference Learning and Intelligent Optimization (LION 2011)",
• year = "2011",
• editor = "Carlos A. {Coello Coello}",
• volume = "6683",
• series = "Lecture Notes in Computer Science",
• pages = "503--506",
• address = "Rome, Italy",
• month = jan # " 17-21",
• note = "Selected Papers",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-25565-6",
• DOI = "doi:10.1007/978-3-642-25566-3_39",
• size = "4 pages",
• abstract = "This work introduces a new technique for features construction in classification problems by means of multi objective genetic programming (MOGP). The final goal is to improve the generalisation ability of the final classifier. MOGP can help in finding solutions with a better generalisation ability with respect to standard genetic programming as stated in [1]. The main issue is the choice of the criteria that must be optimised by MOGP. In this work the construction of new features is guided by two criteria: the first one is the entropy of the target classes as in [7] while the second is inspired by the concept of margin used in support vector machines.",
• affiliation = "Dipartimento di Informatica, Sistemistica e Comunicazione (DISCo), Universita degli Studi di Milano-Bicocca, 20126 Milan, Italy",
• bibdate = "2011-11-16",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/lion/lion2011.html#CastelliMV11",

}

Genetic Programming entries for Mauro Castelli Luca Manzoni Leonardo Vanneschi

Citations