Multiple feature construction in classification on high-dimensional data using GP

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{Tran:2016:SSCI,

• author = "Binh Tran and Mengjie Zhang and Bing Xue",
• title = "Multiple feature construction in classification on high-dimensional data using {GP}",
• booktitle = "2016 IEEE Symposium Series on Computational Intelligence (SSCI)",
• year = "2016",
• month = "6-9 " # dec,
• address = "Athens, Greece",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-5090-4241-8",
• DOI = "doi:10.1109/SSCI.2016.7850130",
• abstract = "Feature construction and feature selection are common pre-processing techniques to obtain smaller but better discriminating feature sets than the original ones. These two techniques are essential in high-dimensional data with thousands or tens of thousands of features where there may exist many irrelevant and redundant features. Genetic programming (GP) is a powerful technique that has shown promising results in feature construction and feature selection. However, constructing multiple features for high-dimensional data is still challenging due to its large search space. In this paper, we propose a GP-based method that simultaneously performs multiple feature construction and feature selection to automatically transform high-dimensional datasets into much smaller ones. Experiment results on six datasets show that the size of the generated feature set is less than 4percent of the original feature set size and it significantly improves the performance of K-Nearest Neighbour, Naive Bayes and Decision Tree algorithms on 15 out of 18 comparisons. Compared with the single feature construction method using GP, the proposed method has better performance on half cases and similar on the other half. Comparisons between the constructed features, the selected features and the combination of both constructed and selected features by the propose method reveal different preferences of the three learning algorithms on these feature sets.",
• notes = "Also known as \cite{7850130}",

}

Genetic Programming entries for Binh Ngan Tran Mengjie Zhang Bing Xue

Citations