Secondly, the decision tree algorithm is optimized in this paper in two aspects: attribute reduction and pruning. Attribute reduction algorithm ER based on the degree of dependency of attribute and post-pruning algorithm Prune based on rough set theory are proposed.
其次,从属性约简和剪枝两方面对决策树算法进行优化,提出了基于属性依赖度的属性约简算法ER和基于粗糙集理论的决策树后剪枝算法Prune。
参考来源 - 基于决策树的数据挖掘算法研究与应用·2,447,543篇论文数据，部分数据来源于NoteExpress
This paper is a brief survey of several methods for decision tree simplification, including the pre-pruning, post-pruning and the other methods.
论文是决策树简化方法的一个综述，包括预剪枝、后剪枝和其它方法。
This avoid high cost by using post-pruning measure which require many times for scanning disk data and amount of CPU time. So we gain a high efficiency.
这避免了后剪枝策略所需的高昂代价，减少了扫描磁盘数据的次数和大量的CPU时间，进一步提高了算法的效率。
A post pruning procedure is designed to deal with the overfitting problem, and two criteria that are the minimum covering rate and the minimum error rate are defined.
同时，基于最小覆盖率和最小错误率给出了一种克服过学习问题的后处理方法。
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