搜索资源列表
C4.5算法
- 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
c4.5-win
- windows操作系统下的决策树分类算法工具包，经典的C4.5算法实现，功能巨强大！-windows operating system under the decision tree classification algorithm tool kit, the classical algorithm C4.5, functional Giant powerful!
ID3+C4.5
- 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.
my.rar
- 自己写的，基于C4.5的数据额挖掘算法，有训练和测试训练集，学习数据挖掘的好程序样例！,Wrote it myself, based on the amount of C4.5 data mining algorithm, a training and testing of training set, a good learning process of data mining sample!
c45.rar
- 这是数据挖掘中c4.5分类算法的vc++源码。,This is a data mining algorithm c4.5 classification of vc++ source code.
matlab
- 决策树C4.5和CART算法的m源码 -CART decision tree algorithm C4.5 and the source m
DataCheck
- 入侵检测数据检测算法，根据C4.5源码改编-Intrusion detection data detection algorithm, in accordance with C4.5 source adaptation
Kode-Program-Algoritma-C4.5
- C4.5 is an algorithm used to generate a decision tree. C4.5 is an extension of Quinlan s earlier ID3 algorithm. The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical class
C4.5
- 这是决策树算法C4.5的源代码！是用vc编写的，内容比较详细。-this is a source code of C4.5 algorithm！
C4.5-by-CPP
- win下C++实现C4.5算法,图形界面具有测试功能.采用悲观后剪枝,使用增益比进行连续属性离散化.-Win C++ C4.5 algorithm under realization, graphic interface with test function. After the pessimistic pruned, use than to gain discretization.
The-introduction-of-C4.5-algorithm
- 介绍C4.5的文章，有详细的例子，对理解算法很有帮助-The article introduces C4.5, detailed examples, helpful to understand the algorithm
c4.5-C
- The aim of this article is to show a brief descr iption about the C4.5 algorithm, used to create Univariate De- cision Trees. We also talk about Multivariate Decision Trees, their process to classify instances using more than one attribute per node i
C4.5
- 这是介绍c4.5算法的一篇文章，非常清楚-It is an article about c4.5 algorithm,which is quite clear.
C4.5
- 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
C4.5-master
- java code for c4.5 algorithm
C4.5
- 自己用VC6.0实现的机器学习十大算法中的c4.5算法，经过测试，算法运行很好-VC6.0 with their own machines to learn the ten algorithms in the c4.5 algorithm, tested, the algorithm runs very well
C4.5
- C4.5算法的matlab实现，里面有标准数据集作为实例进行演示-C4.5 algorithm matlab implementation, which has a standard data set as an example to demonstrate
C4_5
- 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)
08060888
- 实现了C4.5算法的全部功能，并包括设计文档和源程序。(It implements all the functions of the C4.5 algorithm and includes the design of documents and source programs.)
train_C4_5
- matlab编码实现C4.5算法的分类问题，完整代码(Classification of C4.5 algorithm by coding)