Using genetic programming for context-sensitive feature scoring in classification problems

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

@Article{journals/connection/NeshatianZ11,

• author = "Kourosh Neshatian and Mengjie Zhang",
• title = "Using genetic programming for context-sensitive feature scoring in classification problems",
• journal = "Connection Science",
• year = "2011",
• number = "3",
• volume = "23",
• pages = "183--207",
• month = sep,
• keywords = "genetic algorithms, genetic programming, feature scoring, feature ranking, feature selection, classification",
• URL = "http://www.tandfonline.com/doi/abs/10.1080/09540091.2011.630065",
• URL = "http://www.tandfonline.com/doi/pdf/10.1080/09540091.2011.630065",
• DOI = "doi:10.1080/09540091.2011.630065",
• size = "25 pages",
• abstract = "Feature scoring is an avenue to feature selection that provides a measure of usefulness for the individual features of a classification task. Features are ranked based on their scores and selection is performed by choosing a small group of high-ranked features. Most existing feature scoring/ranking methods focus on the relevance of a single feature to the class labels regardless of the role of other features (context-insensitive). The paper proposes a genetic programming (GP)-based method to see how a set of features can contribute towards discriminating different classes. The features receive score in the context of other features participating in a GP program. The scoring mechanism is based on the frequency of appearance of each feature in a collection of GP programs and the fitness of those programs. Our results show that the proposed feature ranking method can detect important features of a problem. A variety of different classifiers restricted to just a few of these high-ranked features work well. The proposed scoring-ranking mechanism can also shrink the search space of size O(2 n ) of subsets of features to a search space of size O(n) in which there are points that are very likely to improve the classification performance.",
• bibdate = "2011-12-01",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/connection/connection23.html#NeshatianZ11",

}

Genetic Programming entries for Kourosh Neshatian Mengjie Zhang

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