基于稀疏矩阵结构的特征选择算法现状研究  

Recent Research of Feature Selection Algorithms Based on Sparse Matrix Structure

作　　者：钟静[1] 方冰 朱江[1] ZHONG Jing;FANG Bing;ZHU Jiang(Army Command College of the PLA,Nanjing 211899,China)

机构地区：[1]中国人民解放军陆军指挥学院,南京211899

出　　处：《信息网络安全》2024年第3期352-362,共11页Netinfo Security

基　　金：国家自然科学基金[71401177]。

摘　　要：在信息时代,数据获取方式简单快捷,使得数据量呈指数型增长。然而这些数据往往是多源高维的,增加了模型的复杂度,容易造成模型过拟合,并且数据中存在的冗余特征会降低模型分类精度。特征选择算法旨在通过去除不相关、冗余或嘈杂的特征,从原始特征中选择一小部分最有效特征,达到降维的效果。目前特征选择算法种类繁多,其中,基于稀疏矩阵结构的特征选择算法由于具有模型简单易懂和易求解的特点而被学者们广泛关注。本文归纳总结了基于稀疏矩阵结构的特征选择算法分类,重点介绍了鲁棒特征选择模型和多视图特征选择模型。首先,介绍了基于稀疏矩阵结构的特征选择算法基本框架;然后,介绍了基于稀疏矩阵结构的一般模型、鲁棒特征选择模型、多视图的特征选择模型,比较了它们在解决目前特征选择算法研究难点中存在的优势和不足;最后,对基于稀疏矩阵结构的特征选择算法进行了总结。文章阐明了理论研究中存在的问题和难点,探讨了基于稀疏矩阵结构的特征选择算法发展思路。In the information age,data acquisition methods are simple and fast,resulting in an exponential growth in data volume.However,these data are often multi-source and high-dimensional,which increases the complexity of the model and can easily lead to overfitting of the model,and the redundant features in the data can reduce the classification accuracy of the model.The feature selection algorithm aims to reduce dimensionality by removing irrelevant,redundant,or noisy features and selecting a small subset of the most effective features from the original ones.At present,there are various types of feature selection algorithms,among which the feature selection algorithm based on sparse matrix structure is widely studied by scholars due to its simple and easy to understand model and easy to solve characteristics.This article summarized the classification of feature selection algorithms based on sparse matrix structures,with a focus on robust feature selection models and multi view feature selection models.Firstly,the basic framework of feature selection algorithm based on sparse matrix structure was introduced;Secondly,the general model based on sparse matrix structure,robust feature selection model,and multi view feature selection model were introduced respectively,and their advantages and disadvantages in solving the current research difficulties of feature selection algorithms were compared.Finally,a summary of feature selection algorithms based on sparse matrix structures was provided.The article elucidates the problems and difficulties in theoretical research,exploring the development ideas of feature selection algorithms based on sparse matrix structures.

关 键 词：稀疏矩阵结构 特征选择 降维 分类 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]