计算机工程与应用2019，Vol.55Issue(2)：21-27,7.DOI:10.3778/j.issn.1002-8331.1809-0149
全局调距和声特征选择算法
Feature Selection Based on Global Pitch Adjusting Harmony Search Algorithm
摘要
Abstract
Feature selection technology can effectively solve the curse of dimensionality problem, and many search strate-gies have been applied to feature selection problems. Aiming at the low search ability of harmony feature selection algo-rithm, an improved Harmony Search Feature Selection algorithm based on self-adaptation Global Pitch Adjusting(HSFS-GPA) is proposed to enhance the exploitation ability of solution space. The distance between feature sets is introduced into the feature selection problem. In the algorithm search process, a new harmony is generated by combining with the global information. The distance between the candidate harmony and the current optimal harmony or the worst harmony is changed. At the same time, competition selection mechanism is established to improve solution precision and enhance the ability of escaping local optima, the information of the worst harmony in harmony memory is updated at each iteration. HSFS-GPA is compared with the original harmony feature selection algorithm, particle swarm optimization algorithm and genetic algorithm. The size of the feature subset selected by HSFS-GPA is reduced by 15% than that of the original harmony search algorithm, and the average of the subset evaluation is increased to 0.98. The experimental result shows that HSFS-GPA can search for a better feature subset under the same condition.关键词
和声搜索/特征选择/启发式算法/维数约减/大数据Key words
harmony search/feature selection/meta heuristics/dimension reduction/big data分类
信息技术与安全科学引用本文复制引用
侯屿,秦小林,彭皓月,张力戈..全局调距和声特征选择算法[J].计算机工程与应用,2019,55(2):21-27,7.基金项目
浙江省高等教育教学改革项目(No.jg2015224). （No.jg2015224）
