Improved SPRINT Algorithm and Its Application in the Physical Data Analysis

In order to determine the human physical condition using the conventional tested data quickly and accurately, this paper proposed a trend selection based scalable parallelizable induction of decision trees algorithm (TESTSPRINT) , based on the concept of pure interval and trend selection method.We can create a human physical condition decision tree quickly based on the basic test data such as height, weight and grip strength, according to the decision tree we can determine human physical health status quickly.Theoretic analysis and experimental demonstrations show that the algorithms proposed in this paper outperforms existing algorithms in time and space complexity, and it was proved fruitful applications in the decision human physical health status with high accuracy.