The research of decision tree mining based on Hadoop
Lu Qiu, Xiaohui Cheng · 2012
For a single node massive data, the mining calculation of the decision-tree is very large. In order to solve this problem, this paper proposes the HF_SPRINT parallel algorithm that bases on the Hadoop platform. The parallel algorithm optimizes and improves the SPRINT algorithm as well as realizes the parallelization. The experimental results show that this algorithm has high acceleration ratio and good scalability.