特征选择
计算机科学
选择(遗传算法)
优化算法
特征(语言学)
人工智能
模式识别(心理学)
算法
数学优化
数学
语言学
哲学
作者
Hongwei Chen,Yajun Hou,Qixing Luo,Hongyu Zhou,Lingyu Yan
标识
DOI:10.1109/icaci.2018.8377518
摘要
This paper starts from the perspective of the entire impacts of text features to classification results, and present a method of text feature selection that based on Water Wave Optimization (WWO) algorithm, Water Wave Optimization Text Feature Selection (WWOTFS), mining text feature selection rules by using Water Wave Optimization algorithm. WWOTFS firstly selects text features by using Chi-square Test, then screens the selected text features by using WWO algorithm. WWOTFS regards a water wave as a feature selection candidate solution, the candidate solutions correspond to the water wave cluster, the accuracy rate is used for fitness function, and the method of grouping is used to lower the dimension of the water wave. The experimental results show that the effect of WWOTFS is better than the traditional feature selection method, and it has good stability.
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