山西大学学报（自然科学版）2024，Vol.47Issue(1)：1-8,8.DOI:10.13451/j.sxu.ns.2023135
基于互信息和遗传算法的特征选择算法
Feature Selection Algorithm Based on Mutual Information and Genetic Algorithm
摘要
Abstract
A novel feature selection algorithm using mutual information and genetic algorithm is presented in this paper.The algo-rithm designed the metrics for measuring the correlation between features and that between features and classes based on mutual in-formation.By combining the strong global optimization capability of genetic algorithms,it can search for a globally optimal feature subset in the candidate feature space,characterized by low inter-feature correlation,high feature-to-class correlation,and high classi-fication accuracy.In this paper,comparative experiments were conducted on 10 standard datasets using 8 correlation-based feature selection algorithms.Under 3 classifiers,the algorithm proposed in this paper achieves average classification accuracies of 88.98%,87.5%,and 86.95%,respectively,outperforming all the comparative algorithms.The experimental outcomes demonstrate the effec-tiveness of the proposed algorithm in significantly reducing the dimensionality of the original feature sets while enhancing the accu-racies of classifiers.关键词
特征选择/相关性/熵/互信息/遗传算法Key words
feature selection/correlation/entropy/mutual information/genetic algorithm分类
信息技术与安全科学引用本文复制引用
张婧,曹峰,董毓莹,张超,余银中,唐超..基于互信息和遗传算法的特征选择算法[J].山西大学学报（自然科学版）,2024,47(1):1-8,8.基金项目
国家自然科学基金(62072291 （）
62272284) （）
安徽省自然科学基金(2008085MF202) （2008085MF202）
