搜索资源列表
C4.5
- 决策树经典学习算法,C4.5算法是ID3算法的改进,加上了子树的信息,因素属性的值可以是连续量,训练例的因素属性值可以是不确定的,对已生成的决策树进行裁剪,减小生成树的规模.-Decision tree learning algorithm of C4.5 algorithm is the classic, the improved ID3 algorithm, coupled with the subtree of the information, the factor attribute v
Decision_making_tree
- 机器学习课本中的未剪枝决策树代码实现,可以直接运行,自行根据书中(西瓜书)表进行建表,输出结果为层次遍历。(Machine learning textbooks do not prune decision tree code, you can run directly, according to the book (watermelon book) table built table, the output results for the hierarchical traversal.)
C4.5决策树
- C4.5决策树的MATLAB实现。内有英文和中文混合注释(C4.5 Decision Tree It has English and Chinese Both Zhu Shi)
UntitledjueceshuID3
- 决策树ID3算法示例,帮助初学者,共同进步(Id3 algorithm example)
牙刷data
- 之前一个牙刷项目中涉及磁力计用到的东西,使用决策树生成的分类器,初级版本。(A primary version of the classifier generated by decision trees.)
trees
- 用PYTHON实现的决策树算法,简单明了,结构清晰(decision tree by python)
DicisionTree
- 决策树算法的简单实现,决策树(Decision Tree)是一种简单但是广泛使用的分类器。通过训练数据构建决策树,可以高效的对未知的数据进行分类。决策数有两大优点:1)决策树模型可以读性好,具有描述性,有助于人工分析;2)效率高,决策树只需要一次构建,反复使用,每一次预测的最大计算次数不超过决策树的深度。(A simple implementation of decision tree algorithms, decision tree (Decision Tree) is a simple b
IDL-decision_tree
- IDL中没有能调用决策树的函数,本程序可以调用决策树工具(d)
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
jueceshu
- 基于vc++的决策树算法,可以进行编译修改(Vc++ based decision tree algorithm, you can compile and modify)
id3决策树
- 一个很好的关于决策树的算法matlab实现,由详细注释,易懂。(A good decision tree algorithm, matlab implementation, by detailed notes, easy to understand.)
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)
Program3-RanShu
- 实现决策树算法 深度学习 。。。。。。。。。。。(decision tree learning)
pres
- 三种分类器:决策树分类器,k-NN分类器和k-means分类器的运行时间以及运行准确率的比较。(Three kinds of classifiers: decision tree classifier, k-NN classifier and K-means classifier running time and accuracy comparison.)
tree
- 使用决策树对存储器进行分类并预测隐形眼镜类型(The classification of memory and prediction of contact lens type using decision 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)
51622453code
- 模式识别的第二次作业,有关使用决策树来进行男女生的分类问题。(The second job of pattern recognition involves the use of decision trees to classify male and female students.)
01决策树分类问题:预测销量高低
- 用python决策树分类问题:预测销量量的高低问题(Decision tree classification problem using Python: forecasting the volume of sales)
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)