Research on feature selection algorithm based on mutual information and genetic algorithm

Panshi Tang, Xiaolong Tang, Zhongyu Tao, Jian-ping Li
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引用次数: 10

Abstract

The wide application of Internet technology and media technology produces more and more data which also leads the arrival of the era of big data. However, it is difficult to extract the needed information from the original data directly except some special conditions. In recent years, the development of machine learning which provide a effective way to solve this problem for us. You can obtain lower rate of Miscalculate when you select a reasonable feature selection algorithm under the premise of not increasing the complexity of algorithm. At present it is divided into two categories named the Filter and Wrapper feature selection algorithm in the field of machine learning. This paper considers both the advantages and disadvantages of these two feature selection algorithm and studies the combined feature selection algorithm.
基于互信息和遗传算法的特征选择算法研究
互联网技术和媒体技术的广泛应用产生了越来越多的数据,这也导致了大数据时代的到来。但是,除了一些特殊的条件外,很难直接从原始数据中提取所需的信息。近年来,机器学习的发展为我们解决这一问题提供了有效的途径。在不增加算法复杂度的前提下,选择合理的特征选择算法,可以获得较低的误算率。目前在机器学习领域分为Filter和Wrapper两大类特征选择算法。本文综合考虑了这两种特征选择算法的优缺点,研究了组合特征选择算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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