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.


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    Title :

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



    Published in:

    Advanced Materials Research ; 734-737 ; 2978-2982


    Publication date :

    2013-08-16


    Size :

    5 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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