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City innovation capability evaluation method based on support vector machine

Yong-li Zhang, Yan-wei Zhu

China will develop into an innovative country in 2020. It has become an important topic that study on evaluation method of innovation ability. But the science and technology innovation capacity determination is complex, there are many factors affecting the innovation ability, there are a non-linear relationship, uncertainty and ambiguity. Support vector machine is a statistical learning method based on small samples, using structural risk minimization principle, and it is good generalization ability. This paper uses support vector regression algorithm to evaluate the ability of innovation of science and technology, get the support vector machine regression model, Through the 2013 yearbook data analysis of the experimental results, this method is achieved very good results in evaluation of regional innovation capacity.