Multi-Classification Combination Algorithm Based on Logit Model and Support Vector Machine

被引：3
|
作者：
Zhang, Xinlei [1 ]
Li, Menggang [2 ]
Zhang, Zuoquan [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Sci, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Sch Econ & Management, Beijing 100044, Peoples R China
来源：
RESOURCES AND SUSTAINABLE DEVELOPMENT, PTS 1-4 | 2013年 / 734-737卷
关键词：
Logit Regression; Support Vector Machine; Principal Component Analysis; Multi-classification Algorithm;
D O I：
10.4028/www.scientific.net/AMR.734-737.2978
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
According to the basic theories of Logit regression analysis and support vector machine, this article involves improved multi-classification combination algorithm. When applying this model, there are some innovations. First, choose optimized composite indicator as a variable through principal component analysis and get more information. Second, introduce Logit parameter model to the quadratic to increase prediction accuracy. Third, put forward a multi-classification combination model of improved Logit model with SVM to increase prediction accuracy.
引用
收藏
页码：2978 / +
页数：2
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