山西大学学报（自然科学版）2025，Vol.48Issue(1)：66-76,11.DOI:10.13451/j.sxu.ns.2024149
基于加权集成的序贯三支决策情感分类
Sentiment Classification Using Sequential Three-way Decisions Based on Weighted Ensemble
摘要
Abstract
To improve the performance of sentiment classification,this paper proposes a sentiment classification model based on weighted ensemble sequential three-way decision.The model firstly uses different classifiers to obtain their respective prediction probabilities for the boundary domain of the review dataset.Then,based on historical classification performance,the prediction prob-abilities of different classifiers are weighted and integrated.According to the threshold and cost loss,three-way decisions are made to classify the reviews into positive,negative,and boundary domains.The boundary domain is sequentially subjected to integrated probability prediction and further classified into new positive,negative,and boundary domains according to the probabilities and thresholds.Until the finest granularity of the boundary domain is reached,a final classification result is obtained through integrated two-way decision.The research results show that this model outperforms existing methods on Chinese computer reviews,hotel re-views and clothing reviews datasets.Among them,the classification accuracy on the hotel review data set reached 86.75％,which was improved by 3.6％compared with the sequential three-branch decision emotion classification based on hard voting integration.关键词
多粒度分类/机器学习/集成学习/文本粒化/粗糙集Key words
multi-granular classification/machine learning/integrated learning/text granulation/rough set分类
信息技术与安全科学引用本文复制引用
帅常朗,钱进,周川鹏..基于加权集成的序贯三支决策情感分类[J].山西大学学报（自然科学版）,2025,48(1):66-76,11.基金项目
国家自然科学基金(62066014,62466017) （62066014,62466017）
江西省自然科学基金项目(20232ACB202013) （20232ACB202013）
