计算机与现代化Issue(2)：66-70,5.DOI:10.3969/j.issn.1006-2475.2018.02.014
文本分类中特征权重算法改进研究
Research on Improvement of Feature Weights in Text Classification
摘要
Abstract
In order to overcome the shortcomings of traditional TF-IDF (Term Frequency Inverse Document Frequency) algorithm,the improved TF-IDF-dist algorithm is proposed by using the distribution of feature words.The experimental results show that the improved algorithm has an average increase of F1 value by 3.2％ in the different feature dimensions.With the different feature selection algorithm,the F1 value is increased by 2.75％ and the improved TF-IDF-dist algorithm has more adaptability on the imbalance datasets.It shows the validity of the algorithm in text classification.关键词
机器学习/文本分类/特征权重/TF-IDFKey words
machine learning/text classification/feature weights/TF-IDF分类
信息技术与安全科学引用本文复制引用
李鹏鹏,范会敏..文本分类中特征权重算法改进研究[J].计算机与现代化,2018,(2):66-70,5.基金项目
陕西省科技厅工业攻关项目(2017GY-070) （2017GY-070）
