decision tree for optimization software 最优化软件中的决策树
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
We'll discuss validation sets when we look at decision trees because they are a common optimization for decision tree learning.
当我们在后面具体提及决策树时，将会进一步讨论验证集，因为它通常是决策树学习的最优选择。
A combined optimization decision tree algorithm suitable for a large scale and high dimension data-base is presented.
提出了一种适合于大规模高维数据库的组合优化决策树算法。
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