决策树与人工神经网络的对比分析

Comparison and Analysis Decision Trees to Artificial Neural Networks for Data Classification

决策树和人工神经网络是数据挖掘分类任务中两项重要技术,各具特点,对不同的数据类型应采用不同的算法进行相应的研究应用。为了深入地说明各自的特点,根据决策树C 4.5算法的原理和流程,以及人工神经网络的BP网络模型原理和实现分类的流程,并应用具体的实例,对两种技术进行了对比分析研究,得出并验证了它们在实现分类中的一些性能差异。

Decision Trees and Artificial Neural Networks are two important technologies of Data Mining in data classification. They have different characteristics of their own, so we should use different algorithms with different data types for application and researches. To explain their own characteristic concretely, this paper studies and analyses in contrast, get and prove some performance differences in data classification, by C4.5 Algorithm and BP Neural Network.