Abstract
Innovation system efficiency analysis and prediction play an important role in regional innovation systems development and improve benefit of innovative capacity for country. According to the county innovation system data which is large scale and imbalance, this paper presented a support vector machine model to predict county innovation system efficiency. The method was compared with artificial neural network, decision tree, logistic regression and naive Bayesian classifier regarding county innovation system efficiency prediction for 83 Chinese counties. It is found that the method has the best accuracy rate, hit rate, covering rate and lift coefficient, and provides an effective measurement for county innovation system efficiency prediction.
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