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Description: Quinlan s C4.5 算法的实现-the implementation of C4.5
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Size: 2048 |
Author: g |
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Description: 数据挖掘算法，分类树的C4.5算法，用于模式分类-data mining algorithms, the C4.5 classification tree algorithm for pattern classification
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Size: 2048 |
Author: sah |
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Description: 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve
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Size: 2048 |
Author: 利军 |
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Description: 决策树技术之ID3以及C4.5算法学习，很有用哦-decision tree technology and C4.5 ID3 algorithm learning useful oh
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Size: 114688 |
Author: 唐稍逊 |
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Description: c4.5主要函数的matlab实现，简单易懂，扩展性很强-c4.5 main function of the Implementation of Matlab, simple, strong expansion
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Size: 2048 |
Author: 郝琳 |
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Description: ID3+C4.5的源程序。用于数据挖掘决策算法的一个实例。-ID3 C4.5 of the source. Data Mining for a decision algorithm examples.
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Size: 5120 |
Author: 张飞 |
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Description: [数据挖掘]数据挖掘部分算法的matlab实现 C4_5
比较经典的代码-[Data Mining] part of data mining algorithms compare classic C4_5 realize matlab code
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Size: 10240 |
Author: fff |
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Description: 用matlab语言写的C4.5算法,用于模式分类-Matlab language used to write the C4.5 algorithm for pattern classification
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Size: 2048 |
Author: 罗升阳 |
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Description: 数据挖掘部分算法的matlab实现 C4_5
大家可以共同研究研究-Data mining algorithm matlab part we will be able to realize C4_5 Research
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Size: 2048 |
Author: lady |
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Description: 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。此外，C4.5只适合于能够驻留于内存的数据集，当训练集大得无法在内存容纳时程序无法运行。-C4.5 algorithm has the following advantages: the classification rules easier to understand, accurate and a higher rate. Its shortcomings are as follows: in the tree structure, the need for a number of data sets the order of scanning and sorting, thus leading to inefficient algorithms. In addition, C4.5 can only be applied to the presence of a data set in memory, when the training set too great to accommodate in memory when the program can not run.
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Size: 1024 |
Author: xinyuanwo |
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Description: 数据挖掘中的c4.5算法
给予决策树-Data Mining in the given decision tree algorithm c4.5
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Size: 3072 |
Author: gezn |
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Description: 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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Size: 8192 |
Author: |
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Description: 决策树C45，用matlab编写的，数据挖掘算法。-Decision Tree C45, prepared by matlab, data mining algorithms.
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Size: 2048 |
Author: 来海锋 |
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Description: 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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Size: 4096 |
Author: 凌风 |
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Description: 数据挖掘matlab源码，包含机器学习领域中经典算法如ID3,C4.5,NN,CARD,EM等.-Data Mining matlab source, including the field of classical machine learning algorithms such as ID3, C4.5, NN, CARD, EM, etc..
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Size: 651264 |
Author: liu yihao |
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Description: 这是一个用matlab编写的C4.5算法的实现-this is a classification of machine learing,C4.5,using matlab
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Size: 2048 |
Author: dupei |
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Description: C4.5算法 matlab实现的，感觉还可以，大家可以看看！-the implementation of C4.5 using matlab
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Size: 2048 |
Author: dizhaung |
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Description: 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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Size: 2048 |
Author: 赵小天 |
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Description: 能够实现几种经典的分类算法（ID3，C4.5等）-It can inmplement several classic classification algrorithm(ID3，C4.5,etc.)
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Size: 661504 |
Author: zhangjunpeng |
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Description: c4.5 algorithm in matlab
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Size: 2048 |
Author: panshopr |
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