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。
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。
An intelligent mining system is created based on the decision tree algorithm.
基于分类决策树算法，建立了一个挖掘体系。
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 thesis compares and analyzes the typical decision tree algorithms, the ID3 algorithm and C4.
本文比较和分析了几种典型的决策树算法，着重对ID 3算法和C4。
Second, this paper proposes a new decision tree algorithm, AF algorithm, which avoids multivalue bios.
提出了一种避免了多值偏向问题的决策树算法——AF算法；
Then, the paper emphasizes the theory and method of Decision Tree algorithm and realizes C4. 5 algorithm.
随后，着重分析了决策树算法的理论背景以及实现步骤，并给出了C4.5算法的伪码实现。
This essay is researching the Decision Tree Algorithm of Data Mining and the use in the Customer Drain analysis.
本文主要是研究数据挖掘中的决策树算法以及决策树算法在具体的小灵通流失分析中的研究与分析。
This paper will explain the process of constructing the test node and propose a two-stage decision tree algorithm.
本文将从几何学角度说明构造测试节点的过程，提出了一种两阶段决策树的算法。
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。
Results The decision tree algorithm ID3 and C4.5 for medical image data mining are realized, the experiment results are given.
结果实现了ID3和C4.5算法对图像数据的分类，获得了分类的实验结果。
There are many classification methods to forecast such as decision tree algorithm (C4.5), Bayes algorithm, BP algorithm and SVM.
现有的分类预测的方法有许多种，常见的有决策树算法(C4.5)、贝叶斯分类算法、BP算法与支持向量机等。
The decision tree algorithm including several classifiers was put forward, which can extract water bodies effectively and easily.
经过研究，发现用决策树分类方法，在各节点设计不同的分类器，可以有效地提取山区中的水体。
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。
Decision tree algorithm is that the category knowledge of the training set is mined through built high precision and small-scale decision tree.
决策树算法通过构造精度高、小规模的决策树采掘训练集中的分类知识。
As for the problem above, the paper in-depth researches one of the core algorithms which are applied to classification-decision tree algorithm.
本文从这一实际问题出发，对数据挖掘中用于分类的核心算法之一——决策树方法进行了深入地研究。
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。
To make more scientific decision, an improved decision tree algorithm weighted ID3 is proposed and applied into the determination of aluminum tapping volume.
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。
Typically, the fuzzy decision tree algorithm is an improvement of the crisp decision tree algorithm, and is an extension of the crisp decision tree algorithm.
通常，模糊决策树算法是在清晰决策树算法的基础上进行改进得到的，是对清晰决策树算法的扩展。
Experiment is the traditional method for analysing multivalue BIOS of decision tree algorithm, but it has a fault that we must have the expertise of the specific field.
实验方法是分析决策树算法中的多值偏向问题的传统方法，其缺点是需要具备该数据领域的专家知识。
And on other hand, the thesis also analyzes the factors that affect the jobs of graduated student by adopting decision tree algorithm, and some valuable models are achieved.
另一方面，本文还利用决策树算法，对影响学生就业的因素进行了分析，得到了一些有价值的模式。
Intelligent evaluation model for air quality based on C4.5 decision tree algorithm is established through the historical data of air pollutants and air quality classes in this article.
本文采用C4.5决策树算法构建空气质量评价系统，挖掘空气污染物和空气等级关系的历史数据，建立空气污染物-空气等级智能评价模型。
Therefore, It possesses important theoretic and practical significance to make further improvement of decision tree algorithm, make it more suitable for data mining application requirements.
因此，进一步改进决策树算法，使其更加适合数据挖掘的应用要求，具有重要的理论和现实意义。
Information gain is the measurement of the attributes selection in classical decision tree algorithm-ID3, but the attributes with high information gain is not always the valuable attributes.
传统的ID3决策树算法以信息增益作为属性选择的准则值，但是信息增益大的属性并不一定就是有价值的属性。
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。
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。
Induction learning of decision tree based on ID3 algorithm is an important branch of inductive learning now, which can be used to automatic acquisition of knowledge.
基于ID 3算法的决策树归纳学习是归纳学习的一个重要分支，可用于知识的自动获取过程。
Induction learning of decision tree based on ID3 algorithm is an important branch of inductive learning now, which can be used to automatic acquisition of knowledge.
基于ID 3算法的决策树归纳学习是归纳学习的一个重要分支，可用于知识的自动获取过程。
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