搜索资源列表
DecisionTree-in-cSharp
- C sharp描述的决策树代码,α-β剪枝算法等,希望能有帮助。-C sharp code described in the decision tree, α-β pruning algorithm, hoping to help.
Water-Demand--System
- 利用彭曼公式开发了作物灌水量决策支持系统,该系统可判断作物的灌水量。-Development of the crop using Penman-type irrigation decision support system, the system can determine the irrigation of crops.
Text2
- 这是一个关于用id3算法实现决策树的源代码-This is a decision tree algorithm id3 about using the source code
fenleisuanfa
- 分别采用感知机算法、最小平方误差算法、线性SVM算法设计分类器,分别画出决策面,并比较性能。-Perceptron algorithm were used, the least square error algorithm, linear SVM classifier algorithm, respectively, making face paint, and compare performance.
DTree
- 决策树算法。 决策树算法。 决策树算法。-Decision tree algorithm. Decision tree algorithm. Decision tree algorithm. Decision tree algorithm. Decision tree algorithm.
decision_tree
- 决策树是一种典型的机器学习。本文档详细介绍了决策树的建立、检测。-Decision tree is a typical machine learning. This document details the establishment of decision tree, testing.
ID3-java-
- ID3决策树算法的JAVA实现.详细的实现过程:熵值条件熵,节点选择等。-ID3 decision tree algorithm JAVA implementation. Detailed implementation process: entropy conditional entropy, the node selection.
Decision_MakingPTree
- 决策树算法案例 对于初学者掌握决策树算法有很大的帮助-Case of decision tree algorithms decision tree for beginners to master a great help
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
test_object
- 高级信息提取 基于专家知识的决策树分类 -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), definitions and rules to build decision trees
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
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
粗糙集全部算法
- 实现了粗糙集的全部算法,从属性约简到决策规则的产生,并且内附测试数据,可以和数据库直接链接。
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.)
FullBNT-1.0.4
- 创建你的第一个贝叶斯网络 手工创建一个模型 从一个文件加载一个模型 使用 GUI 创建一个模型 推断 处理边缘分布 处理联合分布 虚拟证据 最或然率解释 条件概率分布 列表(多项式)节点 Noisy-or 节点 其它(噪音)确定性节点 Softmax(多项式 分对数)节点 神经网络节点 根节点 高斯节点 广义线性模型节点 分类 / 回归树节点 其它连续分布 CPD 类型摘要 模型举例 高斯混合模型 PCA、ICA等 专家系统的混合 专家系统的分等级混合 QMR 条件高斯模型 其它混合模型 参数学
最小错误率贝叶斯决策
- 基于最小错误率的贝叶斯决策 (1)要决策分类的类别数是一定的;(2)每一类出现的“先验概率”已知;(3)每一类的“类条件概率密度”已知;(Bayesian Decision Based on Minimum Error Rate(1) the "prior probabilities" of each class are known; (2) the "conditional probability density" of each class is kn
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.)
decision
- DSmT理论中的决策规则函数源码,对于信息融合的应用有一定的参考价值,尤其对应于冲突性数据。(DSmT theory of decision rule function source code, for the application of information fusion has some reference value, especially in conflict with data.)