A Searching Method of Candidate Segmentation Point in SPRINT Classification. (24th October 2016)

• Record Type: Journal Article
• Authors: Wang, Zhihao; Wang, Junfang; Huo, Yonghua; Tuo, Yanjun; Yang, Yang
• Other Names: Liu Bin-Da Academic Editor.
• Is Part Of: Journal of electrical and computer engineering. Volume 2016(2016)
• Publication Date: 2016-10-24
• Subjects: Computer engineering -- Periodicals; Electrical engineering -- Periodicals; 621.3905
• DOI: 10.1155/2016/2168478
• Languages: English
• ISSNs: 2090-0147

Abstract

Abstract : SPRINT algorithm is a classical algorithm for building a decision tree that is a widely used method of data classification. However, the SPRINT algorithm has high computational cost in the calculation of attribute segmentation. In this paper, an improved SPRINT algorithm is proposed, which searches better candidate segmentation point for the discrete and continuous attributes. The experiment results demonstrate that the proposed algorithm can reduce the computation cost and improve the efficiency of the algorithm by improving the segmentation of continuous attributes and discrete attributes.