On an Improved SPRINT Data Stream Online Classification Algorithm
Zhou Hong, Chun Yan Fu, Jia Mei Xue, Yuan Zhi, Jing Shun Liu · Advanced materials research · 2013
Aiming at the characteristics of data stream, the paper presents an incremental decision tree algorithm based on binary-attribute tree on the basis of SPRINT algorithm. The attribute set of this improved algorithm adopts the maximum entropy attribute classification and dynamic storage method of Bayesian method. By using this improved algorithm, static organization form of candidate attributes set for traditional SPRINT algorithm has been changed and it is much more suitable for concept drift and reduces the time complexity for new sampling insertion and best division node selection as well as saves storage space and increases classification efficiency.