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计算机人工智能方面的决策树方法 c4.5-the decision tree method Bank
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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
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决策树技术之ID3以及C4.5算法学习,很有用哦-decision tree technology and C4.5 ID3 algorithm learning useful oh
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c4.5决策树的实现,应用于一个医学诊断-Bank Decision Tree realized, used a medical diagnosis
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c4.5的源码决策树最全面最经典的版本-Bank of the most comprehensive source of decision tree of the most classic version
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以从医院病案室获得的3022例数据为样本,在完成样本数据库以及糖尿病并发症的多维数据集设计后,以糖尿病并发症流行病学知识发现为重点,研究定性数据定量化挖掘模型及算法引擎的设计与实现,即将关联模型引入糖尿病并发症的流行病学研究.运用决策树技术对数据样本进行分析,采用C4.5找到最优决策树-cases from the hospital to obtain the data for 3,022 cases samples the completion of the sample database a
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这是一个有关决策树分类器中C4.5算法的原程序-This is a decision tree classifiers on which the original algorithm C4.5 procedures
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本程序是用java语言编写的数据挖掘分类算法中的决策树分类方法c4.5程序代码-this procedure is used java language classification of data mining algorithms decision tree classification code Bank
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此代码是用c语言编写的决策树的c4.5代码,它是数据挖掘分类算法中的一种,可以对给定数据集进行分类,挖掘出规则-this code is c language of the decision tree Bank code, which is data mining classification algorithm of a can of a given data set for classification, tapping rules
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C4. 5 决策树展示算法的设计,
C4. 5 决策树展示算法的设计-C4. 5 shows the decision tree algorithm design, C4. 5 shows Algorithm for Decision Tree
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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
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功能强大的决策树回归算法,是C4.5的改进版本,但在精度,速度和内存开销上均有了很大的改进。目前由rulequest公司管理,其可执行程序版本为商业版本,此GPL许可的源代码对外发布。-Powerful decision tree regression algorithm is an improved version of C4.5, but in the precision, speed and memory overhead has been greatly improved. Curren
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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
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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
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decision tree learning for C4.5
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C4.5算法是机器学习算法中的一种分类决策树算法,其核心算法是ID3算法.
-C4.5algorithm is a kind of machine learning algorithm of decision tree classification algorithm, the algorithm is the core of ID3 algorithm.
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决策树分类的各种代码,包括ID3、c4.5等等,有界面可以运行-Various code of decision tree classification, including ID3, C4.5 and so on, there are interface can run
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数据挖掘-决策树-c4.5算法的java代码实现-Data Mining- Decision Tree algorithm java code-c4.5
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数据挖掘-决策树c4.5的c语言代码实现-Data mining- a decision tree c4.5 c language code
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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
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