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应用模糊支持向量机进行英文情感分类
English Emotion Classification Based on Fuzzy Support Vector Machine
【摘要】 针对英文情感分类问题,对不同样本采用不同权重,通过引入模糊隶属度函数,通过计算样本模糊隶属度确定样本隶属某一类程度的模糊支持向量机分类算法,通过对比选取不同核函数和不同惩罚系数的结果.仿真实验结果表明应用模糊支持向量机进行英文情感分类具有较好的分类能力和较高的识别能力.
【Abstract】 For the problem of English emotion classification,different weights for different samples,with the introduction of fuzzy membership functions,using fuzzy support vector machine(FSVM) classification algorithm of samples by calculating the fuzzy membership degree to determine the samples belonging to one kind of degree.By comparing the selection of different kernel functions and different punishment coefficient.The simulation experiment results has proven that FSVM has better classifying ability and higher recognition.
【关键词】 支持向量机;
模糊支持向量机;
英文情感分类;
【Key words】 support vector machine(SVM); fuzzy support vector machine(FSVM); English emotion classification;
【Key words】 support vector machine(SVM); fuzzy support vector machine(FSVM); English emotion classification;
【基金】 黑龙江省哲学社会科学研究项目扶持共建项目,项目名称:基于模糊支持向量机的英语语篇情感分析(13E024)
- 【文献出处】 数学的实践与认识 ,Mathematics in Practice and Theory , 编辑部邮箱 ,2016年01期
- 【分类号】TP391.1;TP18
- 【被引频次】4
- 【下载频次】99