搜索资源列表
C4_5
- C4.5决策树matlab程序,本人找了很久才找到,绝对能用-C4.5 Decision Tree code
mill
- 包含了很多分类算法,有SVM,knn,决策树等,还有文档说明-Contains a lot of classification algorithms, there is SVM, knn, decision tree and so on, have documented
CART
- 决策树算法的CART算法,用MATLAB编写,能有,不错的。-CART decision tree algorithm algorithm, using MATLAB to prepare, to have, good.
SLIQ
- SLIQ数据挖掘算法,使用c++实现,使用SLIQ算法,用信息熵的方法作为决策树节点列策略-SLIQ data mining algorithms using c++ implementation
ID3
- 决策树算法 经典的ID3算法 用于决策树规则学习等等 在规则学习以及分类中有重要的作用-classic decision tree mode for classification and rule learning
1
- 论述了医学图像挖掘在计算机辅助诊断中的作用,提出了采用灰度级作为 CT 图像特征的思想、灰度级的提取和存储方法,介绍 了采用决策树分类算法和基于密度的聚类算法对胸部和头部 CT 图像进行分类和聚类的结果及其分析,给出了分析的结论和进一步的研究方向。-Image mining Computer-aided diagnoses Luminance grade Classification Clustering
jueceshu
- 从网络上搜集的决策树源码,包括C4_5、ID3、CART_iris三个源码,供大家一起学习研究。-Decision tree collected from the network source, including C4_5, ID3, CART_iris 3 source for study and research with everyone.
ID3(MATLAB)
- ID3决策树算法,实现不同条件下数据的分类-ID3 decision tree algorithm, the classification of data under different conditions
decision_tree
- 自己用matlab实现的决策树仿真的代码,决策树代码包含ID3算法和C4.5算法,算法原理可以参照统计学习(李航著),具体代码编写部分参照网上博客。实现结果用matlab的treelayout实现,模拟树形实现最大程度图形化还原,可以为学习相关算法的朋友提供参考。代码包含相应的主函数和两个决策树函数,具体可参考文字示意。(Reference statistics learning (Li Hang) a book to achieve the MATLAB simulation code, th
C4_5
- 决策树分类算法C4.5的matlab代码实现,可返回训练集和测试集的结果,有详细注释(classification tree)
决策树
- 决 策 树 模 型决策树(Decision Tree)是在已知各种情况发生概率的基础上,通过构成决策树来求取净现值的期望值大于等于零的概率,评价项目风险,判断其可行性的决策分析方法,是直观运用概率分析的一种图解法。(The decision tree (Decision Tree) is the basis of probability in the known situations, through the form of decision tree to calculate
chapter28
- 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)
Class_8
- 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)
CART
- 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)
ID3
- 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.)
MATLAB
- 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
决策树C4.5算法matlab源代码(完美运行)
- 可以完美的实现用于统计学习的算法C4.5分类,完整的matlab程序(Classification of algorithm C4.5 for statistical learning)
C4.5
- 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)
matlab-rrt-variants
- 使用rrt随机决策树进行3d路径规划,效果很好(3-D Path Planning Using Random Decision Tree)
matlab实现的C4.5分类决策树算法
- C4.5决策树分类算法,用于进行数据分类(Classification algorithm)