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.
Multi-Classification Combination Algorithm Based on Logit Model and Support Vector Machine
Advanced Materials Research ; 734-737 ; 2978-2982
2013-08-16
5 pages
Article (Journal)
Electronic Resource
English
Data classification with support vector machine and generalized support vector machine
American Institute of Physics | 2017
|Elsevier | 1989
|New Algorithm of Fuzzy Support Vector Machine for Classification with Outliers
British Library Online Contents | 2007
|Mixed Logit (or Logit Kernel) Model: Dispelling Misconceptions of Identification
Online Contents | 2002
|