针对传统的决策树生成算法之不足，提出了两种改进算法。
Two improved algorithms for decision tree generation are proposed. The efficiency of the improved algorithms are verified.
文章针对传统的决策树生成算法之不足，提出了两种改进算法。
Two improved deci-sion tree generation algorithms are proposed. The efficiency of improved algorithms are verified.
通过应用实例比较分析，证明该算法能生成最小化决策树，并且决策树生成规则切合实际。
The comparable and analyzable experiment shows that this algorithm can make a minimize decision tree whose rules are true.
为提高决策的科学化程度，提出了一种改进的决策树生成算法加权id3，并将其应用于铝电解生产中出铝量的设定。
To make more scientific decision, an improved decision tree algorithm weighted ID3 is proposed and applied into the determination of aluminum tapping volume.
在第二类拓扑查询中，现有的决策树生成算法假定所有拓扑关系拥有相同的出现率，这种情况在实际中是非常少见的。
Existing decision tree building algorithm assumes that all topological relations occur with equal probability, but this situation is extremely rare in practice.
通过对决策树算法的深入分析，我们围绕着C4.5决策树生成算法建立了一个分类预测系统并实现了与劳动力市场信息管理系统（LMIS）的集成。
With the thorough analysis on the algorithm of decision tree induction, we established a classification and prediction system based on C4.5 and accomplished the integration with the LMIS system.
通过对训练数据的学习，生成用于轨道故障判决的决策树(或者规则)。
The decision tree (or rules) used for rail deformation detection was generated by learning the train data.
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.
运用云神经网络学习变量间的云映射关系，从中生成云决策树。
It adopts cloud neural network to study the cloud mapping relationship between variables, so as to generate cloud decision tree.
提出了一种融合无监督和监督两种学习策略生成多分类决策树的方法。
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification decision tree.
用该方法生成的决策树规模小且计算复杂度低，但是泛化能力不佳。
The method can learn smaller trees with lower computational complexity, but its generalization ability is not better.
并描述了从组织协作网到决策树的生成过程，对生成过程的求解采用了优化协作树算法。
The process of generating decision making tree from collaboration net is presented and the algorithms to optimize collaboration tree are adopted to construct the best decision making tree.
文中主要讨论如何应用C4.5算法构造列车轨道故障检测的决策树以及根据生成的决策树实现轨道故障的判决。
This paper mainly discusses how to build a decision tree of rail deformation detection by using C4.5 algorithm and how to make decision of the rail deformation by building decision tree.
大型复杂系统的故障隔离是系统维修的重要环节，现有的故障隔离算法存在平均故障隔离时间（MFIT）长，不能快速自动生成决策树等缺点。
Long mean fault isolation time (MFIT) and being incapable of quickly automatic building of FI decision-making tree are the disadvantages of existing methods.
用新的属性选择标准生成的决策树一般具有叶子数目较少，叶子的平均深度也较小，且叶子具有较强的泛化能力。
The decision tree constructed with the new standard of attribute selection has the following characteristics: fewer leaf nodes, fewer levels of average depth, better generalization of leaf nodes.
结果：生成一棵具有5个叶结点的3级决策树，分析得到的5条规则能有效预测住院患者的住院天数。
Results: Generated a 3-level decision tree with 5 leaves and discovered 5 rules which can effectively predict the hospitalization days.
结果：生成一棵具有5个叶结点的3级决策树，分析得到的5条规则能有效预测住院患者的住院天数。
Results: Generated a 3-level decision tree with 5 leaves and discovered 5 rules which can effectively predict the hospitalization days.
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