搜索资源列表
c4.5.rar
- 通过C4.5 的实现可以进行构建决策树 来进行有效的分类,Through the realization of C4.5 decision tree can be constructed to carry out an effective classification
c4.5java
- 决策树分类算法,c4.5,java语言进行描述的-Decision tree classification algorithm, c4.5, java language described
file
- c++ 实现 决策树 分类算法,规模很小但是很简练的一个算法-c++ realization of the decision tree classification algorithm, the size of a small but very concise algorithm for
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
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
id3matlab
- id3算法用MATLAB实现决策树分类器程序。-id3 decision tree!
C4_5
- c4.5经典算法,实现决策树分类功能,可以对连续数值和离散数值实现很好的分类,并有剪枝功能-c4.5 classic algorithms, to achieve the decision tree classification, can be continuous and discrete numerical values to achieve good classification, and a pruning function
Application_of_Decision_Trees_on_uncertain_data.ra
- 决策树分类算法在不确定型数据方面的应用,首先进行学习,然后进行分类-Application of Decision Trees on uncertain data
id
- 决策树Id3算法,基于决策树的分类算法,包含注释-fbjdhuieher
ID3
- ID3算法是数据挖掘中常用的算法,属于决策树分类算法,其分类速度较快,尤其对于大规模数据。-ID3 algorithm is commonly used in data mining algorithms, decision tree classification algorithm is, the classification speed, especially for large-scale data.
test_draworb0
- 高级信息提取 基于专家知识的决策树分类:规则获取(经验总结、数据挖掘如c4.5 cart算法)、规则定义以及构建决策树 -Advanced information extraction based on expert knowledge of the decision tree classification: the rules to get (lessons learned, data mining algorithms such as c4.5 cart), definit
chengxu
- 决策树分类,id3算法,数据挖掘,以学生成绩为例-Decision tree classification, id3 algorithm, data mining, to student achievement, for example
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)
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)
id3决策树——new
- 这是一个ID3决策树分类的代码用于分类器的计算,大家下载类以后可以学习使用,ID3是一种比较古老的决策树,最新的有C4.5等(This is an ID3 decision tree classification code for classifier calculation, which can be used after downloading the class. ID3 is a relatively ancient decision tree, with the latest C4.5
决策树java代码1
- 决策树可对数据进行分类,选出最大增益属性。(Decision tree can be classified data, select the maximum gain attribute.)
决策树与随机森林
- 给出对决策树与随机森林的认识。主要分析决策树的学习算法:信息增益和ID3、C4.5、CART树,然后给出随机森林。 决策树中,最重要的问题有3个: 1. 特征选择。即选择哪个特征作为某个节点的分类特征; 2. 特征值的选择。即选择好特征后怎么划分子树; 3. 决策树出现过拟合怎么办? 下面分别就以上问题对决策树给出解释。决策树往往是递归的选择最优特征,并根据该特征对训练数据进行分割。(The understanding of decision tree and random
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)
决策树训练及分类
- 该压缩包包括两个文件: 1、main.m 将训练数据输入到决策树中,训练并在自动分好的测试数据上测试,并保存训练好的决策树 ctree.mat文件。 2、classification.m 加载训练好的决策树,使用决策树对新输入的数据进行分类。 该方法主要用于对SLIC超像素块进行分类,稍加修改可以用于其他数据分类。(The compression package consists of two files: 1. Main. m inputs training data into decisio
决策树分类实验(乳腺癌)
- 决策树分类程序,包含使用的数据集和运行结果(Decision tree classifier, including data sets used and running results)