This paper introduces two construction algorithms of Classification decision tree based on parallel algorithm, and analyzes applicability.
本文重点介绍了两种基于并行算法的分类决策树的构造算法，并对它们的适用性及特点作了分析。
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification 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。
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。
Classification (also known as classification trees or decision trees) is a data mining algorithm that creates a step-by-step guide for how to determine the output of a new data instance.
分类(也即分类树或决策树)是一种数据挖掘算法，为如何确定一个新的数据实例的输出创建逐步指导。
Note that this type of training will generally fit into the decision problem framework because the goal is not to produce a classification but to make decisions that maximize rewards.
需要注意的是，这类训练通常会置于决策问题的框架里，因为它的目标不是产生一个分类系统，而是做出最大回报的决定。
The second was classification (also known as classification tree or decision tree), which can be used to create an actual branching tree to predict the output value of an unknown data point.
第二种技术是分类（即分类树或决策树），用来创建一个实际的分支树来预测某个未知数据点的输出值。
Launch the workbench and export the knowledge base and decision plan to your IBM InfoSphere Classification Module server.
启动工作台并将知识库和决策计划导出到IBMInfoSphereClassificationModule服务器。
Decision tree algorithms are applied to the data mining of the mammography classification, proposes a medical images classifier based on decision tree algorithm, the experiment results are given.
利用决策树算法对乳腺癌图像数据进行分类，实现了一个基于决策树算法的医学图像分类器，获得了分类的实验结果。
Under the condition of unchanged classification and decision abilities, attribute reduction is to delete irrelative or unimportant attribute.
属性约简要求在保持知识库的分类和决策能力不变的条件下，删除不相关或不重要的属性。
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。
Decision tree is one of the models that are often used in classification, and it has been widely researched and applied since it was proposed in 1966.
决策树是分类中常用的模型之一，自1966年被提出以来已经得到了广泛的研究和应用。
Two methods for automatic classification and decision of Doppler waveforms for flow sonography analysis system are described.
本文介绍了两种对超声多普勒血流声谱国进行波形自动分类决策的方法。
In this paper, a novel decision table discretization algorithm is presented, which has fine attribute reduction function in time of data discretization and increases quality of classification.
本文提出了一个新的决策表离散化算法，该算法在离散化数据的同时具有良好的属性约简功能。
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。
The system USES the method of facing illation classification to achieve the design of all the process decision illation modules.
系统按正向分级推理的方法实现了工艺决策推理各功能模块的设计。
Discusses the classification and regression trees method, introduces its application in developing universities 'science research decision support system.
讨论了分类回归树方法，并介绍了它在开发高校科研决策支持系统中的应用。
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。
There are some various algorithms in data mining, and decision tree classification algorithm is the most popular one.
在数据挖掘中存在多种算法，决策树分类算法是应用比较多的一种。
This paper introduces the classification model of random decision tree and how to heuristic selected the depth and the number, the experiment shows that the algorithm is effectiveness and efficiency.
该文介绍了随机决策树分类模型及如何启发式选择随机决策树的深度及棵树，通过实验证明了该算法的有效性和高效性。
Data mining is an important problem in KDD, and Rough set as a theory of set with fuzzy boundary is widely applied to infer classification rules from decision system.
数据挖掘是知识发现领域的一个重要问题，粗糙集理论是一种具有模糊边界的数据挖掘方法，它被广泛应用于决策系统的分类规则提取中。
Methods: After literature search and analysis, the authors introduced the decision body, classification and contents of international Grading Nursing system.
方法：通过文献检索和实证研究，从分级护理的决策主体、分类、内容等方面对国外分级护理进行介绍。
Then the decision tree and class association rules mining are used on the video attribute database to extract a decision tree classification rule set and a class association rule set respectively.
然后分别使用决策树、分类关联规则等技术对视频属性数据库进行数据挖掘，提取出决策树分类规则集和分类关联规则集；
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。
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。
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。
In order to improve the classification quality of decision system, a strategy of data mining classification rules based on rough approaching approximation measurement in data ware is proposed.
为了提高决策系统的分类质量，探讨了一种在数据仓库中基于粗糙逼近近似度量的挖掘分类规则策略。
Moreover, this thesis compares FCA with clustering analysis, and analyzes the similarities and differences of classification based on concept lattice and decision tree.
另外，本文在相关章节对形式概念分析和聚类分析进行比较以及分析总结了基于概念格的分类和决策树分类法的异同。
Meanwhile it describes the decision tree classification algorithm in detail, analyzes the ID3, C4.5 and other prevalent decision tree algorithm.
同时详细的阐述了决策树分类算法，并对比较流行的决策树算法id3、C4.5等算法进行详细分析与比较。
In the end, decision tree classification experiments results and contrastive precision accuracy are obtained.
最后进行了分步决策树分类实验和与传统分类方法的精度对比分析。
In the end, decision tree classification experiments results and contrastive precision accuracy are obtained.
最后进行了分步决策树分类实验和与传统分类方法的精度对比分析。
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