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采用动态相关度权重的特征选择算法

许华杰 刘冠霆 张品 秦远卓

计算机工程与应用2024,Vol.60Issue(4):89-98,10.
计算机工程与应用2024,Vol.60Issue(4):89-98,10.DOI:10.3778/j.issn.1002-8331.2306-0230

采用动态相关度权重的特征选择算法

Feature Selection Algorithm Using Dynamic Relevance Weight

许华杰 1刘冠霆 2张品 3秦远卓4

作者信息

  • 1. 广西大学 计算机与电子信息学院,南宁 530004||广西大学 广西多媒体通信与网络技术重点实验室,南宁 530004
  • 2. 广西大学 计算机与电子信息学院,南宁 530004
  • 3. 北部湾港防城港码头有限公司,广西 防城港 538001
  • 4. 广西大学 土木建筑工程学院,南宁 530004
  • 折叠

摘要

Abstract

When considering the new classification information provided by the candidate features,the features selection algorithm based on mutual information usually ignores that the addition of the candidate features will cause the change of the correlation between the selected features and class labels,which will bring additional new information;in addition,when calculating redundant information,using the form of cumulative summation may lead to the underestimation of the redundancy degree of candidate features.In view of the above problems,the definition of dynamic relevance weight is proposed to more comprehensively consider the new information components brought by candidate features.The im-proved definition of redundant items is proposed,and the maximum and normalization strategy are adopted to solve the problem of underestimating redundancy.On this basis,the feature selection using dynamic relevance weight(FSDRW)is proposed.Five current mainstream filter-based feature selection algorithms based on mutual information are selected for comparative experiments.Experiments on machine learning test datasets from UCI(University of California Irvine)and ASU(Arizona State University)show that the proposed algorithm works well in classification accuracy and comprehen-sive performance.Finally,the proposed algorithm is applied to the recognition of microseismic and blasting signals in a reservoir project in Guangxi.The selected features of the algorithm are used for microseismic signal recognition,achieving a classification accuracy of 98.86%,verifying the effectiveness of the algorithm in practical applications.

关键词

特征选择/互信息/信息熵/动态相关度权重

Key words

feature selection/mutual information/information entropy/dynamic relevance weight

分类

信息技术与安全科学

引用本文复制引用

许华杰,刘冠霆,张品,秦远卓..采用动态相关度权重的特征选择算法[J].计算机工程与应用,2024,60(4):89-98,10.

基金项目

国家自然科学基金(71963001) (71963001)

广西科技计划项目(2017AB15008) (2017AB15008)

崇左市科技计划项目(FB2018001). (FB2018001)

计算机工程与应用

OA北大核心CSTPCD

1002-8331

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