GP-决策树优化算法 GP-decision tree optimization algorithm
A detailed survey of all the decision tree optimization approaches is given, such as modifying test space, modifying test search, tree pruning, restricting database and alternating data structures.
对现有的各类决策树优化技术进行了详细的介绍,如修改测试属性空间、改进测试属性选择方法、决策树的剪枝、对数据进行限制和改变数据结构等,并介绍了每种方法中比较经典的算法。
参考来源 - 基于粗糙集合理论的决策树优化方法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
基于上述分析，提出了决策树优化算法。
Based on the above analysis, a new algorithm of decision tree induction is proposed.
在这个过程中，应用了决策树归纳学习的优化原则，使得生成的决策树能最简洁、准确地描述神经网络学到的知识。
In the process of constructing tree, three optimization principles are adopted to concisely and accurately describe the knowledge that the networks have learned.
其次，在解决工艺参数优化的问题中，本文提出了一种正演的方法，即结合使用决策树分类器以及人工神经网络进行综合分析的方法来完成。
Secondly, in solving the problem that the craft parameter is optimized, this paper has put forward a method to perform, which using decision tree and ANN carry on comprehensive.
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