计算机与数字工程2024，Vol.52Issue(6)：1612-1616,1675,6.DOI:10.3969/j.issn.1672-9722.2024.06.004
二进制鼠群优化算法的特征选择及数据分类
Feature Selection and Data Classification of Binary Rat Swarm Optimization Algorithm
摘要
Abstract
In view of the difficulty of improving classification accuracy and reducing the number of feature selection in feature selection technology,with the increase of data dimension,this paper improves the new bionic optimization algorithm mouse swarm optimization algorithm,introduces the conversion function into the algorithm,uses the K-nearest neighbor method as the classifier,and proposes a binary mouse swarm optimization algorithm for feature selection and data classification,effectively reduces the di-mension of features and the error rate of data classification.It is tested on 10 data sets of UCI and compared with genetic algorithm,particle swarm optimization algorithm,bottle sea squirt swarm optimization algorithm and sine cosine algorithm.The simulation re-sults show that the algorithm can improve the accuracy of data classification and effectively reduce the feature dimension.The algo-rithm has good convergence and robustness.关键词
鼠群优化算法/特征选择/数据分类/K近邻Key words
rat swarm optimization/feature selection/data classification/KNN分类
信息技术与安全科学引用本文复制引用
鲍美英,申晋祥..二进制鼠群优化算法的特征选择及数据分类[J].计算机与数字工程,2024,52(6):1612-1616,1675,6.基金项目
国家自然科学基金项目(编号:11971277) （编号:11971277）
山西省教育厅科技创新项目(编号:2019L0738) （编号:2019L0738）
山西大同大学科研项目(编号:2020k10) （编号:2020k10）
山西大同大学云冈专项项目(编号:2020YGZX016) （编号:2020YGZX016）
山西大同大学校级教学改革创新项目(编号:XJG2023246,XJG2023251)资助. （编号:XJG2023246,XJG2023251）
