一种基于改进SLIQ决策树分类算法的应用研究  

Decision Tree Algorithm Application for Classification in Data Mining Based on Extended SLIQ Algorithm

作　　者：张薇[1,2] 

机构地区：[1]苏州大学计算机科学与技术学院,江苏苏州215006 [2]苏州大学图书馆,江苏苏州215006

出　　处：《苏州大学学报（工科版）》2010年第1期72-77,共6页Journal of Soochow University Engineering Science Edition (Bimonthly)

摘　　要：提出了一种改进的SLIQ决策树分类算法,克服了原有SLIQ算法需要大量计算决策树每个节点的吉尼指数(gini index)的缺点。改进的SLIQ算法能够有效地减少计算的复杂度。结合实例,将该算法与原有SLIQ算法和基于人工神经网络的分类算法应用结果进行比较,实验结果表明该算法的分类准确率远远高于SLIQ算法和基于人工神经网络的分类算法。This paper aims at improving the performance of the SLIQ decision tree algorithm （Mehta et. al, 1996） for classification in data mining. An improvement over the SLIQ algorithm has been proposed to reduce the computational complexity. It was observed that the decision tree constructed using the proposed decision tree algorithm gave far better classification accuracy than the classification accuracy obtained using the SLIQ algorithm and the neural network classification technique.

关 键 词：数据挖掘 决策树 SLIQ算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]