Text Classification Research Based on Improved SoftMax Regression Algorithm

被引：1
|
作者：
She, Xiangyang [1 ]
Zhu, Yinglong [1 ]
机构：
[1] Xian Univ Sci & Technol, Coll Comp Sci & Technol, Xian, Shanxi, Peoples R China
来源：
2018 11TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 2 | 2018年
关键词：
Text classification; SoftMax regression; Linear model; Nonlinear model;
D O I：
10.1109/ISCID.2018.10164
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the current SoftMax regression algorithm model, a linear combination of features is used, and the resulting separated hyperplane belongs to a linear model. Aiming at the nonlinear characteristics of text categorization, an improved nonlinear SoftMax regression algorithm is proposed. The algorithm adds the squared term and the multiplicative term of the feature to the linear feature, and obtains the nonlinearly separated hyperplane by solving. Experiments show that the improved SoftMax regression algorithm has higher text classification accuracy than the SoftMax regression algorithm.
引用
收藏
页码：273 / 276
页数：4
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