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。
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。
Multivalue BIOS may result in inducing wrong knowledge from data set, and consequently result in the decline of the performance of decision tree.
多值偏向可能导致从数据集中归纳出错误的知识，使决策树的性能下降。
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。
The decision tree (or rules) used for rail deformation detection was generated by learning the train data.
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)。
Decision Tree is a useful method of data mining.
决策树是数据挖掘中的常用方法。
Decision tree is one of the important Categorising Data Mining methods.
决策树是分类数据挖掘的重要方法。
Aim To study the application of decision tree algorithm for medical image data mining.
目的研究决策树算法在医学图像数据挖掘中的应用。
This paper firstly introduces the principle of Data Mining technology and the decision tree method.
本文首先详细介绍了数据挖掘技术及其中的决策树方法。
Decision tree is a basic learning method in machine learning and data mining.
决策树是机器学习和数据挖掘领域中一种基本的学习方法。
OBJECTIVE To set up the prediction model for evaluating the risk of diabetes mellitus(DM)in community by application of decision tree with data from health records.
目的利用居民健康档案数据和决策树方法，建立糖尿病预测模型，建立社区新型糖尿病高危人群筛选模式。
In data mining, decision tree algorithm is a key research direction.
在数据挖掘中，决策树方法是一个重点研究方向。
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。
Decision tree is a convenient and practical method for data mining.
决策树方法是数据挖掘的一种方便而实用的方法。
Most data mining tools use rule discovery and decision tree technology to extract data patterns and rules; its core is the inductive algorithm.
大部分数据挖掘工具采用规则发现和决策树分类技术来发现数据模式和规则，其核心是归纳算法。
As a basis for the excavation data: data storage building and digging another key technical data: Decision tree in the market forecast quoted.
作为数据挖掘的基础：数据仓库的建立，以及另一项数据挖掘的关键技术：决策树技术在市场预测方面的引用。
Most data mining tools for knowledge discovery generally use rule discovery and decision tree technology to extract data patterns and rules.
用于知识发现的大部分数据挖掘工具均采用规则发现和决策树分类技术来发现数据模式和规则。
This D-S decision tree is a new classification method adapted to the uncertain data.
实验结果表明D- S决策树分类算法能有效的对不确定数据进行分类。
Decision tree is an important method in induction learning as well as in data mining, which can be used to form classification and predictive model.
决策树是归纳学习和数据挖掘的重要方法，通常用来形成分类器和预测模型。
So that it can not only protect the original data effectively, but also not decrease the classified precision of Decision Tree.
这样既可以有效的保护原始数据，又没有降低决策树的分类精度。
About Data Mining ID3 decision tree algorithm code.
说明：关于数据挖掘中的决策树id3算法的代码。
For a given incomplete decision table, the algorithm constructs decision tree using the improved ID3 algorithm, and fills the missing data in the process of constructing the decision tree.
对于给定的不完全决策表，该算法应用改进的ID 3算法来构造决策树，在构造决策树的过程中对遗失值进行补充。
Also, for the continuity in Diabetes Mellitus data, choosing the C4.5 algorithm in Decision Tree method to be the data mining algorithm.
同时，由于糖尿病数据的连续性，选用了决策树方法中的c4.5算法作为数据挖掘算法。
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。
According to the rice spectral features of hyperspectral image data acquired during the rice is growing, a hybrid decision tree classification algorithm dealing with the variety of rice is developed.
根据水稻生长期的高光谱数据的光谱特征，设计了一个混合决策树分类算法。
A data mining process for evaluating the database of stocks by using computational verb decision tree was introduced in brief.
最后简单介绍了利用计算动词决策树对股票价格数据库进行数据挖掘的过程。
After pretreatment, the data were loaded in SQL2000 server database. We established the case mix of the inpatient using the grouping node selected by decision tree.
所有资料经预处理后，导入SQL2000数据库，利用其中的数据挖掘工具——微软决策树进行分类节点变量的选取，以此构建病例组合。
After pretreatment, the data were loaded in SQL2000 server database. We established the case mix of the inpatient using the grouping node selected by decision tree.
所有资料经预处理后，导入SQL2000数据库，利用其中的数据挖掘工具——微软决策树进行分类节点变量的选取，以此构建病例组合。
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