我是靠谱客的博主 温婉冬天,最近开发中收集的这篇文章主要介绍微阵列数据特征选择的模因算法,觉得挺不错的,现在分享给大家,希望可以做个参考。

概述

#引用

##LaTex

@inproceedings{Zhu:2007:MAF:1418707.1418870,
author = {Zhu, Zexuan and Ong, Yew-Soon},
title = {Memetic Algorithms for Feature Selection on Microarray Data},
booktitle = {Proceedings of the 4th International Symposium on Neural Networks: Advances in Neural Networks},
series = {ISNN '07},
year = {2007},
isbn = {978-3-540-72382-0},
location = {Nanjing, China},
pages = {1327–1335},
numpages = {9},
url = {http://dx.doi.org/10.1007/978-3-540-72383-7_155},
doi = {10.1007/978-3-540-72383-7_155},
acmid = {1418870},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
}

##Normal

Zexuan Zhu and Yew-Soon Ong. 2007. Memetic Algorithms for Feature Selection on Microarray Data. In Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (ISNN '07), Derong Liu, Shumin Fei, Zeng-Guang Hou, Huaguang Zhang, and Changyin Sun (Eds.). Springer-Verlag, Berlin, Heidelberg, 1327-1335. DOI=http://dx.doi.org/10.1007/978-3-540-72383-7_155


#摘要

two novel memetic algorithms (MAs)

synergies of Genetic Algorithm (wrapper methods) and local search methods (¯lter methods) under a memetic framework

  1. Wrapper-Filter Feature Selection Algorithm (WFFSA)
  2. Markov Blanket-Embedded Genetic Algorithm (MBEGA)

not significantly statistically di®erent
MBEGA is observed to converge to more compact gene subsets than WFFSA

more suitable gene subset


#主要内容

microarray technology
microarray data

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a balanced .632+ external bootstrap
【1】C. Ambroise, G. McLachlan, Selection bias in gene extraction on the basis of microarray gene-expression data, Proc. Natl. Sci. USA 99 (2002) 6562–6566.

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