搜索资源列表
CART
- 此为机器学习算法中的决策树方法之一CART，也是决策树的基本算法-This is the machine learning algorithm, one of the decision tree method CART, is the basic decision tree algorithm
matlab-C4.5
- 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
GA_SVM
- 对于小样本而言，SVM的仿真效果要比神经网络好，但是SVM的性能依赖于它的两个训练参数，本算法是用GA自动选择SVM的两个参数。-For small sample case, SVM simulation results than the neural network is good, but the performance of SVM depends on its two training parameters, the algorithm is automatically selected
DecisionTreeYSD
- 决策树的Matlab实现，实现了分类问题和回归问题，有很好的调试结果-Matlab implementation of decision trees
ID3-dision-tree-
- matlab 代码 机器学习算法 决策树算法id3算法 -matlab id3 算法
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
Ch03
- 决策树，实例：matlab实现使用决策树顶预测隐形眼镜类型。-Splitting datasets one feature at a time: decision trees
DT
- 基于matlab开发平台的决策树的实现，该算法比较精良容易懂。-the realization of decision tree：Implementation of decision tree based on MATLAB development platform, the algorithm is relatively good
DecisionTree
- 决策树的判别，用于机器学习与模式识别，matlab源代码。-Discrimination tree for machine learning and pattern recognition, matlab source code.
决策树资料合集
- 决策树源文件，实例，内容详解，word文档(Decision tree source file, instance)
决策树源代码合集
- 决策树，源代码，注释和详解，内附加说明，id3，CD_4型决策树(Decision tree, source code, notes and detailed explanation,)
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id3算法matlab代码，已调试，根据需要改写main函数，实现数据分类功能(code for decision tree)
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)
决策树分类代码
- 本代码基于MATLAB平台完成，对图像进行相应的决策树分类(This code is based on the MATLAB platform, for the corresponding decision tree classification)
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
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)