Improved Algorithm of Decision Tree Based on Key Decision Factor and Its Applications in Railway Transportation
Jiansheng Zhu · Journal of the China Railway Society · 2011
According to the analyses on applications of decision tree induction in railways,it is found that there is limitation in analyzing the imbalance-distribution main classes because major voting is selected as its leaf node measure.This paper presents the measure of using the key decision factor to improve the leaf node label measure of the decision tree,which aims at solving the unfair competition among the main classes between the majorities and the minorities for labeling the leaf nodes.This algorithm adapts to proceeding with the huge imbalance ticket datasets and extracts a kind of instructive rules that collect the advantages in both prediction and statistics,therefore it is suitable for supporting multi-level requirements of the decision-makers for predictive analysis.