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Zhigao Zheng
Peking University

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Improved SPRINT Algorithm and its Application in the Physical Data Analysis Yazhi Ding; Zhigao Zheng; Ma Rong
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp6909-6920

Abstract

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