Genetic Programming for Feature Ranking in Classification Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@InProceedings{DBLP:conf/seal/NeshatianZA08,

• author = "Kourosh Neshatian and Mengjie Zhang and Peter Andreae",
• title = "Genetic Programming for Feature Ranking in Classification Problems",
• booktitle = "Proceedings of the 7th International Conference on Simulated Evolution And Learning (SEAL '08)",
• year = "2008",
• editor = "Xiaodong Li and Michael Kirley and Mengjie Zhang and David G. Green and Victor Ciesielski and Hussein A. Abbass and Zbigniew Michalewicz and Tim Hendtlass and Kalyanmoy Deb and Kay Chen Tan and J{\"u}rgen Branke and Yuhui Shi",
• volume = "5361",
• series = "Lecture Notes in Computer Science",
• pages = "544--554",
• address = "Melbourne, Australia",
• month = dec # " 7-10",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-89693-7",
• DOI = "doi:10.1007/978-3-540-89694-4_55",
• abstract = "Feature ranking (FR) provides a measure of usefulness for the attributes of a classification task. Most existing FR methods focus on the relevance of a single feature to the class labels. Here, we use GP to see how a set of features can contribute towards discriminating different classes and then we score the participating features accordingly. 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 FR 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 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 may improve the classification performance.",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• notes = "Features selected by GP fed into: J48 (C4.5), naive Bayes, SMO SVM (Weka, Java). p552 oerformance does _not_ improve montonically with additional (lower ranked) features.",

}

Genetic Programming entries for Kourosh Neshatian Mengjie Zhang Peter Andreae

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