Emotional Text Analysis Based on Ensemble Learning of Three Different Classification Algorithms

Wenshuo Bian, Chunzhi Wang, Z. Ye, Lingyu Yan
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引用次数: 8

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.
基于三种不同分类算法集成学习的情感文本分析
为了提高文本情感分析模型的准确率和泛化性能,本文提出了一种集成学习模型,该模型包括逻辑回归、支持向量机和k邻域算法三种不同的分类算法。与单一分类算法相比,该算法具有更好的准确率。实验结果表明,该模型具有良好的泛化性能和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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