City Scientific and Technological Progress Level Classification Based on Support Vector Machine

City scientific and technological progress level classification and promotion play a central role in spurring city income growth and reducing poverty. Based on the Chinese city data availability, this paper built evaluation index system on the level of city scientific and technological progress. According to the city scientific and technological progress data which is large scale and imbalance, this paper presented a support vector machine model to classify city scientific and technological progress level. The method was compared with artificial neural network, decision tree, logistic regression and naive Bayesian classifier regarding city scientific and technological progress level classification for fourteen Chinese cities. It is found that the method has the best accuracy rate, hit rate, covering rate and lift coefficient, and provides an effective measurement for city scientific and technological progress level classification.