基于XGboost的网络业务类型分类方法

Tiantian Lv, Yanqin Wu, Le Zhang
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引用次数: 0

摘要

以便区分不同类型的网络服务,分析不同类型服务的客户需求,保证用户感知。提出了一种基于XGboost的网络业务类型分类方法。首先提出基于Pearson相关系数的特征贡献分析方法,然后构建基于XGboost的网络业务类型分类模型,对网络业务类型进行分类。最后,利用均方根误差对分类方法进行评价。与其他模型相比,XGboost模型的RMSE不大于3.5,低于LSTM、ARIMA、LR和SVM模型,证明了XGboost模型在网络业务类型分类中的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A classification method of network business type based on XGboost
In order to distinguish different types of network services and analyze the needs of customers of different types of services to ensure user perception. This paper proposes a classification method of network business type based on XGboost. Firstly, a feature contribution analysis method based on Pearson correlation coefficient is proposed, then the classification model of network business type based on XGboost is constructed to classify network business type. Finally, RMSE is used to evaluation the classification method. Compared with other models, the RMSE of XGboost model is no more than 3.5, lower than LSTM, ARIMA, LR and SVM model, which proves the reliability of the XGboost model in network business type classification.
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