{"title":"基于三种不同分类算法集成学习的情感文本分析","authors":"Wenshuo Bian, Chunzhi Wang, Z. Ye, Lingyu Yan","doi":"10.1109/IDAACS.2019.8924413","DOIUrl":null,"url":null,"abstract":"In order to improve the accuracy and generalization performance of text sentiment analysis model, an integrated learning model is proposed in this paper, which includes three different classification algorithms - Logistic regression, support vector machine and K-Neighborhood algorithm. Compared with single classification algorithm, this algorithm shows better accuracy. The experimental results show that the model has good generalization performance and robustness.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Emotional Text Analysis Based on Ensemble Learning of Three Different Classification Algorithms\",\"authors\":\"Wenshuo Bian, Chunzhi Wang, Z. Ye, Lingyu Yan\",\"doi\":\"10.1109/IDAACS.2019.8924413\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the accuracy and generalization performance of text sentiment analysis model, an integrated learning model is proposed in this paper, which includes three different classification algorithms - Logistic regression, support vector machine and K-Neighborhood algorithm. Compared with single classification algorithm, this algorithm shows better accuracy. The experimental results show that the model has good generalization performance and robustness.\",\"PeriodicalId\":415006,\"journal\":{\"name\":\"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAACS.2019.8924413\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2019.8924413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emotional Text Analysis Based on Ensemble Learning of Three Different Classification Algorithms
In order to improve the accuracy and generalization performance of text sentiment analysis model, an integrated learning model is proposed in this paper, which includes three different classification algorithms - Logistic regression, support vector machine and K-Neighborhood algorithm. Compared with single classification algorithm, this algorithm shows better accuracy. The experimental results show that the model has good generalization performance and robustness.