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计算机人工智能方面的决策树方法 c4.5-the decision tree method Bank
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c4.5决策树的实现,应用于一个医学诊断-Bank Decision Tree realized, used a medical diagnosis
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决策树分类算法,c4.5,java语言进行描述的-Decision tree classification algorithm, c4.5, java language described
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quilan的决策树c4.5-r8的windows版本-quilan decision tree c4.5-r8 of the windows version
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C4.5 决策树算法源码。C4.5决策树是决策树领域的经典算法。以其为内容的书籍引用率已经达到一万次以上-C4.5 decision tree
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c45决策树算法,其中输出结果为正确分类率、错误分类率和不可识别率,由c++编写-c45 decision tree,c++
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数据挖掘课中的一个算法c4.5决策树源码,只要有相应的测试文件就可以了-Data mining courses in a decision tree algorithm c4.5 source code, as long as the corresponding test file on it
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决策树c4.5算法的c++实实现 希望对大家有用可直接使用。
-The decision tree c4.5 algorithm c++ implemented to achieve the hope that useful can be used directly.
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用c++编写的决策树识别,数据来源为csdn上一位大神的经典之作-Classic written c++ decision tree identification, data sources from csdn
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决策树算法_C实现,主要是数据挖掘领域。-_C Decision tree algorithm to achieve
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C++编写的C4.5决策树程序,为数据挖掘基础算法。
网址为:http://www.cnblogs.com/michaelGD/archive/2012/11/14/2770758.html-C++ written C4.5 decision tree program, the foundation for the data mining algorithms. Site at: http://www.cnblogs.com/michaelGD/archive/2012/11/14/277
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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
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c4.5决策树批量预测代码,将GetData函数中fallDetect.cases改成想要预测的预测集的名字,在linux下用gcc编译,将main函数中的fallDetect.tree改成你自己的决策树模型的名字,使用前必须在同一目录下放有使用c4.5训练出来的决策树-c4.5 decision tree batch prediction code, the name changed to GetData function fallDetect.cases want to predict th
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C4.5决策树算法java实现,未实现截枝部分-decision tree algorithm
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C4.5决策树算法,C++算法,通过仔细阅读,可以很方便的了解跟学习决策树算法。-C4.5 decision tree algorithm, C++ algorithm, by reading carefully, you can easily understand the decision tree algorithm with learning.
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决策树C4.5程序设计,非常实用且方便,欢迎大家学习,借鉴。-C4.5 decision tree program design, very practical and convenient, welcome everyone to learn from.
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matlab code for C4.5 decision tr-matlab code for C4.5 decision tree
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C4.5算法,优秀的决策树算法,由于求解特征分类问题(C4.5 algorithm, an excellent decision tree algorithm, especially for the problem of feature classification)
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这是一个ID3决策树分类的代码用于分类器的计算,大家下载类以后可以学习使用,ID3是一种比较古老的决策树,最新的有C4.5等(This is an ID3 decision tree classification code for classifier calculation, which can be used after downloading the class. ID3 is a relatively ancient decision tree, with the latest C4.5
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使用matlab实现C4.5决策树算法核心(Implementing the Core of C4.5 Decision Tree Algorithms with MATLAB)
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