搜索资源列表
RoughSet3_1
- java实现的以粗糙集改进的决策树经典算法ID3,并有小实例进行测试,结果正确。-Java realize decision tree classic ID3 algorithm, and a small example to test, the result is correct.
111
- 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. -C4.5algorithm is a kind of machine learning algorithm of decision tree classification algorithm, the algorithm is the core of ID3 algorithm.
decisiontree1
- 使用sql server中的MDX语言直接对数据进行挖掘,采用ID3决策树算法-ID3 decision tree
BIID3_javaa
- 基于决策树的数据挖掘算法,是很不错的的Java版的ID3算法,大家可以看看。 -Decision tree-based data mining algorithms is a very good Java version of the ID3 algorithm, we can see.
MY_ID3
- 这是用C++实现的ID3决策树,决策树算法是非常常用的分类算法,是逼近离散目标函数的方法,学习得到的函数以决策树的形式表示。-ID3 decision tree, the decision tree algorithm implementation in C++ is a very commonly used classification algorithms, approximation discrete objective function, the learning function to
DecisionTree
- 决策树的简单实现,使用ID3作为属性度量选择,测试数据为Jiawei Han数据挖掘书本第六章购物篮数据-Simple implementation of the decision tree using ID3 as an attribute metric selection, test data Jiawei Han data mining the the books Chapter VI basket data
matlab_ID3
- 决策树的ID3算法的源代码,最后是其实验数据,运行很简单!-ID3 decision tree algorithm source code, and finally the experimental data, the run is very simple!
datamining-algorithm
- 数据挖掘的经典算法的java实现,含源码和说明。包括了ID3决策树,贝叶斯分类器等经典算法。-A Java implementation of classic data mining algorithm, including source code and instructions. Including the ID3 decision tree, bayes classifier and classic algorithms.
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
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.
DT
- 关于数据挖掘中的决策树ID3算法的代码。-About Data Mining ID3 decision tree algorithm code.
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
Classifier
- 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
DecisionTreeID3
- 决策树ID3算法的MATLAB程序,这里采用信息增益的方法.-MATLAB program of Decision Tree Algorithm ID3,by the information gain.
DM6_decision_tree
- 实现ID3决策树算法,可以实现基本眜分类,最终的决策树是以结构体存放的-ID3 decision tree
ID3DecisionTree
- 原为某课大作业,改进的决策树函数,使用matlab对ID3决策树算法进行了重现。支持树的建立,打印和使用。附带部分注解-A rewrite of decision tree in matlab.
c4.5
- C4.5是机器学习算法中的另一个分类决策树算法,它是基于ID3算法进行改进后的一种重要算法,相比于ID3算法,改进有如下几个要点:用信息增益率来选择属性.-C4.5 decision tree algorithm is another classification machine learning algorithm, which is based on ID3 algorithm is an important algorithm improved, compared to the ID3 a
LJSDLSD
- 【matlab国外编程代做】id3决策树matlab实现源码 可以作为参考使用 谷速编程-[do] matlab foreign programming generation of ID3 decision tree to achieve matlab source code can be used as reference Valley speed programming
DecisionTree
- 游戏AI介绍及决策树ID3算法的一个实现源码及思维过程。-Game AI introduction and ID3 decision tree algorithm source code and an implementation of the thinking process.
ID3AlgorithmforWeatherJudge
- 讲ID3算法应用于天气决策。给定一组数据集,构建ID3判定树,对某一天气状况进行判断。使用Python脚本编写,C语言版本可参考百度文库(http://wenku.baidu.com/link?url=B3ltO-rUB7K927wLNaGaSInD0hoXRzjVtxFhwcvCdKqewIOu4BZ3SzpC9kRER4qOdBW2_19j-TdYd0H13LJhXZWApI1udXK3wIKBYwso37e),未验证。-Speak ID3 algorithm is applied to w