RETRACTED ARTICLE: Sentiment classification using harmony random forest and harmony gradient boosting machine

被引：0

作者：

K. Sridharan

G. Komarasamy

机构：

[1] Anna University,

[2] Bannari Amman Institute of Technology,undefined

来源：

Soft Computing | 2020年 / 24卷

关键词：

Sentiment analysis (SA); Harmony search (HS) algorithm; Gradient boosting and random forest (RF);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The building of a system for exploring the opinions of users that are made in the blog posts, tweets, reviews or comments regarding a particular topic, policy or a product is known as sentiment analysis. The primary aim of this is the determination of the user attitude regarding a certain topic. The harmony search algorithm has proved to be extremely useful in a varied range of problems in optimization. This shows better performance compared to the other techniques of optimization. Another very powerful technique that is applied to machine learning which is now getting extremely popular is gradient boosting. There are several tree parameters which have been optimized for the random forest and the gradient boosting machine that make use of the harmony search algorithm.

引用

页码：7451 / 7458

页数：7

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[2] RETRACTED: Sentiment classification using harmony random forest and harmony gradient boosting machine (Retracted article. See vol. 27, pg. 1217, 2023)
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