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此为机器学习算法中的决策树方法之一CART，也是决策树的基本算法-This is the machine learning algorithm, one of the decision tree method CART, is the basic decision tree algorithm
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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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decision tree
calculate information gain
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matlab decision tr-matlab decision tree
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实现ID3 决策树算法，并使用MATLAB自带的工具箱函数画出决策树生成相应的规则-Achieve ID3 decision tree algorithm, and using MATLAB toolbox function that comes with the decision tree to generate the appropriate rules to draw
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基于matlab开发平台的决策树的实现，该算法比较精良容易懂。-the realization of decision tree：Implementation of decision tree based on MATLAB development platform, the algorithm is relatively good
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matlab code for id3 decision tr-matlab code for id3 decision tree
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matlab code for C4.5 decision tr-matlab code for C4.5 decision tree
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决策树源文件，实例，内容详解，word文档(Decision tree source file, instance)
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决策树，源代码，注释和详解，内附加说明，id3，CD_4型决策树(Decision tree, source code, notes and detailed explanation,)
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决策树id3算法matlab代码，已调试，根据需要改写main函数，实现数据分类功能(code for decision tree)
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机器学习的决策树问题算法matlab实现，有注释和源码(Machine learning decision tree algorithm matlab implementation, with notes and source code)
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这个是ID3决策树算法的MATLAB代码，主要用于数据分类。(classification of data.)
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介绍决策树与随机森林算法的定义及应用，包含matlab程序(This paper introduces the definition and application of decision tree and random forest algorithm, including Matlab program)
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决策树CART算法源代码，可利用，包括make_tree和use_tree(the code of decision tree CART algorithm including make_tree and use_tree)
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本代码基于MATLAB平台完成，对图像进行相应的决策树分类(This code is based on the MATLAB platform, for the corresponding decision tree classification)
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基于matlab的决策树ID3算法，完成对数据集的分类问题(Based on matlab decision tree ID3 algorithm, the classification of data sets is completed.)
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本书论述在MATLAB环境下如何实现神经网络，包括了常用的神经网络及相关理论，如BP神经 网络、RBF神经网络、SVM、SOM神经网络、灰色神经网络、决策树、随机森林、小波神经网络、NARX神经网络等以及各种优化算法与神经网络的结合。((This book discusses how to realize neural network in MATLAB environment, including the commonly used neural network and related the
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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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