搜索资源列表
c45_vc
- 计算机人工智能方面的决策树方法 c4.5-the decision tree method Bank
weka-3-4-4
- 由java开发的软件包，里面有人工智能所用的很多东东，包括神经网络，支持向量机，决策树等分类和回归分析方法，集成化软件哦！-by java development package, which has artificial intelligence used by many of the Eastern, including neural networks, support vector machines, such as decision tree classification and reg
92
- 本代码是用java语言编写的基于决策树c4.5算法的数据挖掘程序，它可以在很多领域如股票系统中使用 -the code is written in java-based Decision Tree Algorithm Bank data mining process, it can in many areas such as the use of the stock system
C45Driver
- c45决策树改进算法，主要用于数据挖掘中的聚类分析。对从事dm研究的人应该有用-C45 Decision Tree Algorithm, mainly for data mining of cluster analysis. Dm engaged in research should be useful
C45Rule-PANE
- 决策树 C45Rule-PANE算法 解决了决策的问题,是从QUILAN算法修改而成-Decision Tree C45Rule - PANE algorithm to solve the problem of decision-making, from QUILAN algorithm revisions
ID3算法源程序(C语言)
- ID3算法源程序。使用的方法是编写一个*.dat文件保存样本数据，还有一个*.tag文件保存属性列名，且最后一个属性是标号属性。运行是输入id3 文件名。输出格式是一个二叉判定树。-ID3 algorithm source. The method used was to prepare a document preservation *. dat sample data, a document preservation *. tag attributes listed, and the fina
dtview-java
- java语言实现的一个在数据挖掘中能图形化显示决策树分类结果的程序。-java language of a data mining can display graphical decision tree classification procedures.
决策树c4.5-r8的windows版本
- 用c++实现的决策树算法，windows环境下，希望对学习数据结构和算法的朋友有所帮助。-achieve with the Decision Tree Algorithm, windows environment, and I hope to learn from data structures and algorithms friends help.
决策树学习及SEE5的使用
- 数据挖掘分类算法决策树学习算法介绍以及SEE5的使用说明-data mining algorithms decision tree classification algorithm presentations and the use SEE5
C4.5算法
- 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve
ID3_src
- 一个用C＃写的ID3算法，属于数据挖掘中的决策树生成算法。-a C# write ID3 algorithm, data mining is the decision tree generation algorithm.
tree
- Decision Tree id3 which is a system that extracts informative patterns data. Data mining algorithm.And there are several examples.
decision-making-tree
- 决策树的Python代码实现，要所报内含原数据-Decision Tree Python code, containing the original data to be reported
tree
- 用MATLAB实现的决策树，附带有测试代码和数据集。-MATLAB implementation of a decision tree, comes with test code and data sets.
trees
- weka中的决策树分类算法，REPTree，RandomTree，RandomForest(Decision tree classification algorithm in Weka, REPTree, RandomTree, RandomForest)
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)
DL_L1
- 关于最新的python3上的decision tree 的算法(An algorithm for decision tree on the latest python3)
DecisionForest_v3.1
- Decision tree implementation
tree
- 分类决策树的核心思想就是在一个数据集中找到一个最优特征，然后从这个特征的选值中找一个最优候选值，根据这个最优候选值将数据集分为两个子数据集，然后递归上述操作，直到满足指定条件为止。附代码(The core idea of a classified decision tree is to find an optimal feature in a data set, and then find an optimal candidate value from the selected value of
tree
- 决策树 机器学习实战CH03 统计所有label的频次，计算香农熵(Decision Tree Machine Learning Practical Combat CH03 Statistics Frequency of All Labels and Calculates Shannon Entropy)