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C4.5算法进行决策树生成 以信息增益最大的属性作为分类属性，生成决策树，从而得出决策规则。-C4.5 decision tree algorithms to generate information gain the greatest attribute as a classification attributes, generate decision tree, and came to decision-making rules.
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通过C4.5 的实现可以进行构建决策树 来进行有效的分类,Through the realization of C4.5 decision tree can be constructed to carry out an effective classification
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决策树c4.5算法的c++实现 希望对大家有用,C4.5 decision tree algorithm c++ to achieve useful for all of us hope
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C4.5决策树的应用,c45是数据挖掘中重要的决策工具,C4.5 decision tree application
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决策树关联规则比较经典的算法，通常一下大型的应用项目使用，因为其稳定，实用！-Comparison of the classical association rules decision tree algorithm, usually about the use of large-scale application projects, because of its stability, and practical!
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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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决策树 C4.5 分类器, 用java语言写的.大家一起参考一下. -C4.5 decision tree classifier, using the java language. U.S. with reference.
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C4.5决策树matlab程序,本人找了很久才找到，绝对能用-C4.5 Decision Tree code
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c4.5 关于决策树decision tree的matlab实现程序 -c4.5 decision tree decision tree on the realization of the matlab program
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NeC4.5 is a variant of C4.5 decision tree, which could generate decision trees more accurate than standard C4.5 decision trees, through regarding a neural network ensemble as a pre-process of C4.5 decision tree.
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决策树算法C4.5源码,
The directory Data contains some sample datasets. Many interesting data
collections are maintained by the University of California, Irvine, in a
data repository-C4.5 decision tree algorithm source, The directory Data contains so
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this decision tree ID3 algorithm, this algorithm is one of decision tree algorithm like cart, chaid, c4.5, etc-this is decision tree ID3 algorithm, this algorithm is one of decision tree algorithm like cart, chaid, c4.5, etc
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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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机器学习界著名的决策树算法的实现c4.5算法，这是开源的，有兴趣的可以研读-The well-known machine learning algorithm to achieve c4.5 decision tree algorithm, which is open source, could be interested in reading
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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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ID3 决策树的实现 数据挖掘 Dtree4.5-ID3 decision tree data mining Dtree4.5
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基于C4.5的决策树算法，一种非线性分类器-Based on C4.5 decision tree algorithm, a nonlinear classifier
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决策树经典学习算法，C4.5算法是ID3算法的改进，加上了子树的信息，因素属性的值可以是连续量,训练例的因素属性值可以是不确定的,对已生成的决策树进行裁剪,减小生成树的规模.-Decision tree learning algorithm of C4.5 algorithm is the classic, the improved ID3 algorithm, coupled with the subtree of the information, the factor attribute v
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关于决策树C4.5算法的几篇学术论文（基于C4.5算法的遥感影像分类）-Several papers (C4.5 decision tree algorithm C4.5 algorithm based on image classification)
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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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