Description: 该代码是数据挖掘里面的决策树算法 利用ID3理论，通过对训练数据的分析判断，计算出各个数据的其它对目标属性的重要程度，即计算出每个其它数据的信息增益值来将训练数据逐步分类，最后得出目标分类，从而实现决策树的生成过程。最后即可利用此决策树来对新的数据进行测试，判断其目标属性的可能值。-The data mining code is inside the ID3 decision tree algorithm using the theory of training data by analyzing the data to calculate all the other attributes on the target level of importance, that is, every other data to calculate the information gain value to the training data Category gradually came to the conclusion that the target classification, in order to achieve the process of decision tree generation. Finally, you can use this decision tree to test the new data to determine its objectives may be the value of properties. Platform: |
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Description: 该源代码主要实现C4.5决策树算法，C4.5是对ID3算法的一种改进，它完善了ID3算法，补充了其算法的一点不足-The source code is the main achievement of C4.5 decision tree algorithm, C4.5 is an improved ID3 algorithm, which improved the ID3 algorithm, the algorithm added a little less than its Platform: |
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Author:小强 |
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Description: 数据挖掘的经典算法的java实现，含源码和说明。包括了ID3决策树，贝叶斯分类器等经典算法。-A Java implementation of classic data mining algorithm, including source code and instructions. Including the ID3 decision tree, bayes classifier and classic algorithms. Platform: |
Size: 450560 |
Author:ming |
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Description: MATLAB编写的基于决策树的ID3算法实现，模式识别，人脸识别。压缩包中包含两个源文件和测试图片，ID3源文件为主代码，fi为求熵函数。-MATLAB prepared based on the ID3 decision tree algorithm, pattern recognition, face recognition. Compressed package contains two source files and test images, ID3-based source code files, fi for the sake of entropy. Platform: |
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Author:zhanghang |
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Description: C4.5 算法是机器学习算法中的一种分类决策树算法,其核心算法是ID3算法. C4.5算法继承了ID3算法的优点，并在以下几方面对ID3算法进行了改进：
1) 用信息增益率来选择属性，克服了用信息增益选择属性时偏向选择取值多的属性的不足；
2) 在树构造过程中进行剪枝；
3) 能够完成对连续属性的离散化处理；
4) 能够对不完整数据进行处理。
C4.5算法有如下优点：产生的分类规则易于理解，准确率较高。其缺点是：在构造树的过程中，需要对数据集进行多次的顺序扫描和排序，因而导致算法的低效。-The design and implementation of C4.5 and source code,C4.5 algorithm is a classification of the decision tree algorithm of machine learning algorithms, the ID3 algorithm is the core algorithm. Platform: |
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Author:李菲 |
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Description: 游戏AI介绍及决策树ID3算法的一个实现源码及思维过程。-Game AI introduction and ID3 decision tree algorithm source code and an implementation of the thinking process. Platform: |
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Author:wanghongyu |
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Description: 决策树ID3算法实验_数据集car_databases。用python编写的决策树ID3算法，运用了Car-Evaluation的例子。BUG较少，综合了网上的优秀代码，并进一步形成自己的代码。代码基本有注释，风格良好，能够很快看懂。内含有比较规范的报告文档，包含所有流程图，说明图，以及文档风格绝对不错，无需更改，建议下载！
该算法所测试的数据集如下（已经打包在内，并已经生成xls格式，方便直接使用）：
已知：UCI标准数据集Car-Evaluation，定义了汽车性价比的4 个类别；
求：用ID3算法建立Car-Evaluation的属性描述决策树
Car-Evaluation训练数据集文件：
1. car_databases.pdf
2. car_evalution-databases.pdf(Decision tree ID3 algorithm experiment data set car_databases. The decision tree ID3 algorithm written in Python is used in the example of Car-Evaluation. BUG is less, it combines the excellent code on the Internet, and further forms its own code. The code is basically annotated, style is good, and can read quickly. It contains a relatively standardized report document, including all flow charts, illustrations, and document styles. Absolutely, no need to change. We recommend downloading.
The data set tested by this algorithm is as follows (already packaged and has been generated in XLS format for easy use):
Known: the UCI standard dataset Car-Evaluation defines 4 categories of vehicle performance price ratio.
Use ID3 algorithm to build Car-Evaluation attribute description tree.
Car-Evaluation training dataset file:
1. car_databases.pdf
2. car_evalution-databases.pdf) Platform: |
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Author:小强你好 |
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