搜索资源列表
C4_5_explaned
- matlab的一个c4.5实现小程序，（非原创）注意将其中的break改成return，还有一些小瑕疵。-matlab c4.5 applet attention to break into the return, there are some small flaws.
C4.5
- 决策树分类 通过读取数据 求信息增益率选择最好的分离属性-Decision tree classification by reading the data and information gain ratio to select the best separation properties
DecisionTree
- 决策树算法实现，C4.5，挺好的实现了，大家可以下载来-Cnt main(int argc, char* argv[]){ string filename = "source.txt" DecisionTree dt int attr_node = 0 TreeNode* treeHead = nullptr set<int> readLineNum vector<int> readClumNum int deep
demo
- 数据挖掘机器学习中的决策树c4.5的实现源代码，仅供学习-Data mining machine learning to achieve the source code tree c4.5
C4.5
- 决策树算法_C实现，主要是数据挖掘领域。-_C Decision tree algorithm to achieve
machine-learning-2
- 机器学习算法之C4.5与CART，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-The machine learning algorithm C4.5 and CART, the classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
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. 分类决策树算法是从大量事例中进行提取分类规则的自上而下的决策树. -C4.5 algorithm is a machine learning algorithm, a classification decision tree algorithm, the core algorithm is ID3 algorithm classification tree algorithm is extracted from
Text2
- 用java语言实现数据挖掘经典算法之一的C4.5算法。-Using java language Classical data mining algorithms C4.5 algorithm.
DTree
- 一个实现分类决策树算法的系统。ID3算法和C4.5算法。-A decision tree algorithm to achieve classification system. ID3 and C4.5 algorithms.
c45
- 对C4.5程序进行了修改，使代码更加优化-Procedures for C4.5 was modified to make the code more optimized
Matlab
- C4.5的matlab实现，并且进行了详细的注释，并进行了有序化处理-C4.5 matlab realize, and conducted a detailed notes, and conducted an orderly processing
C4_5
- 是一个介绍及其学习算法C4.5的文档，里面讲的比较详细-Is an introduction to its learning algorithm C4.5 of the document, which the more detailed
adaboos
- 当弱分类器算法使用简单的分类方时,boosting的效果明显地统一地比bagging要好.当弱分类器算法使用C4.5时,boosting比bagging较好,但是没有前者的比较来得明显.-When the weak classifier algorithm using simple classification method, boosting the effect clearly uniformly better than bagging. When the weak classifier
DecisionTree
- 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
BI
- BI中的ID3，和C4.5算法的C++具体实现-BI in the ID3, and C4.5 algorithms C++ concrete realization
6ce633e678ee
- ID3和C4.5算法的java实现 数据挖掘算法-ID3 C4.5
J48
- J48算法源代码,WEKA，C4.5算法源代码-J48 algorithm source code
JAVA-decisiontree
- 本程序由Java编写，运行前请确认您的电脑上已安装JDK1.7或以上版本并配置好JDK的系统环境变量。请使用Eclipse集成开发导入源代码-The Algorithm of Decision Trees: ID3 and C4.5
CSDN
- 上传的是CSDN上下的有关代码。里面包含c4.5程序，ID3等相关源代码。这是很有用的代码。-Upload is about code CSDN bottom. Which contains c4.5 program, ID3 and other related source code. It is useful code.
C45
- C4.5是一系列用在机器学习和数据挖掘的分类问题中的算法。它的目标是监督学习：给定一个数据集，其中的每一个元组都能用一组属性值来描述，每一个元组属于一个互斥的类别中的某一类。C4.5的目标是通过学习，找到一个从属性值到类别的映射关系，并且这个映射能用于对新的类别未知的实体进行分类。-C4.5 is used in a series of machine learning and data mining algorithms for classification problems.