• Figure 2-proxy server traversal decision tree.

    图2——代理服务器遍历决策树。

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  • Should you use a rule set or a decision tree to define a group of rules?

    您应该使用规则集或决策树来定义一组规则吗?

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  • Some people find it helpful to make a decision tree, which lays out every possibility in visual format.

    有些人发现列出一张决定树很有帮助,它会以视觉的格式列出每一个可能性。

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  • A decision tree is just a way of diagramming the choices that affect your health and weighing the risks and benefits of each.

    “决策树”仅是一种方法,它罗列出影响你健康的选项,并对每个选项存在的风险和好处进行评估。

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  • By creating a classification tree (a decision tree), the data can be mined to determine the likelihood of this person to buy a new M5.

    创建一个分类树(一个决策树),并借此挖掘数据就可以确定这个人购买一辆新的M5的可能性有多大。

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  • Simplifying trees is the key part of decision tree induction learning.

    树的简化是决策树归纳学习中关键的部分。

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  • An algorithm of the decision tree based on class feature matrix is proposed.

    提出了一种基于类别特征矩阵的决策树算法。

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  • Based on the above analysis, a new algorithm of decision tree induction is proposed.

    基于上述分析,提出了决策树优化算法。

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  • The thesis researches an algorithm based on decision tree classifier for packet filtering.

    本文提出了一种基于决策树分类器的数据包分类算法。

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  • An MSS spectral form correlation model and a histogram decision tree classifier are presented.

    本文提出MSS数据波谱形态相关模型和直方图决策树分类法。

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  • A hierarchical decomposed support vector machines binary decision tree is used for classification.

    采用一种层次分解的支持向量机二叉决策树进行分类识别。

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  • ID3 algorithm is the most basic algorithm in the decision tree learning, and has a wide application.

    ID 3算法是最基本的决策树学习算法,有很广的应用。

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  • In the paper, the problem of freeway incident duration prediction is studied by decision tree method.

    利用决策树方法对高速公路事件持续时间预测问题进行研究。

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  • Minimum entropy is chosen as a heuristic strategy in decision tree (DT) learning algorithm such as ID3.

    决策树的学习算法,比如id3算法,选用最小信息熵作为启发式信息。

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  • This paper proposes an efficient algorithm for constructing decision tree and then mapping it to neural net.

    本文提出一个有效的算法,先构造决策树,然后将构造的决策树转换为神经网。

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  • This paper proposes a text classification method based on Cloud Theory and neural network structure decision tree.

    提出一种基于云理论和神经网络构造决策树的文本分类方法。

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  • The algorithm constructs decision tree using an improved ID3 algorithm, and fills the missing data by decision rules.

    该算法应用改进的ID 3算法来构造决策树,利用决策规则对缺失值进行补充。

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  • Compared with artificial classification, nerve network, and decision tree, its test error is low and the speed is high.

    该方法与人工分类、神经网络、决策树等方法比较,其测试误差低,测试速度高。

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  • Variety bias exists in many decision tree algorithms, and in the past people analyzed this problem mainly based on experiments.

    多值偏向是决策树算法中普遍存在的问题,以往人们对于多值偏向问题的分析主要是基于实验观测的。

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  • The introduction of generalized decision tree(GDT) realized the unification of classification rules and decision tree structure.

    文章引入了广义决策树的概念,实现了分类规则集和决策树结构的统一。

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  • The decision tree is a frequently-used classification method in data mining, it is easy to understand and large in scope to apply.

    决策树是数据挖掘技术中一种常用的分类方法,易于理解,应用范围广泛。

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  • Results indicate that the performance of the metric-based decision tree is some better than that of the conventional decision tree.

    试验结果表明,基于度量的决策树的性能优于传统的决策树。

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  • The choice of attribute selection metric to split has an important impact on the shape and the depth of the resulting decision tree.

    在根据入侵规则构造决策树时,所依据的分类属性选择标准对决策树的形状和深度有很大的影响。

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  • Experimental results show that the choice for trend forecasting models can be correctly finished by using GP-decision tree algorithm.

    实验结果表明,应用GP决策树算法能够正确完成对趋势预测模型的选择。

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  • The style sheet compiler therefore constructs a decision tree which is used at run time to decide which template rule to apply to a given node.

    因此样式表编译器构造了决策树,在运行时用它来决定将哪个模板规则应用于给定节点。

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  • When complex, embedded software is involved, this leads to a many-to-many decision tree with thousands — perhaps millions — of possible allocations.

    当涉及到复杂的、嵌入式软件时,就会导致一个上千——或许上百万种可能分配的多对多决策树。

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  • In the process of constructing a decision tree, the criteria of selecting partitional attributes will influence the efficiency of classification.

    在构造决策树的过程中,分离属性选择的标准直接影响分类的效果。

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  • In the process of constructing a decision tree, the criteria of selecting partitional attributes will influence the efficiency of classification.

    在构造决策树的过程中,分离属性选择的标准直接影响分类的效果。

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