Description: Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
一个可以实现多种方法分类的软件，利用各个
对象的属性。决策树，距离、密度等-Weka is a collection of machine learning al gorithms for data mining tasks. The algorithms can either be applied directly to a dataset or ca lled from your own Java code. Weka contains tool 's for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for d eveloping new machine learning schemes. can be a real Categories are various methods of software, using all the attributes of objects. Decision Tree, distance, density, etc. Platform: |
Size: 15446626 |
Author:马何坛 |
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Description: Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
一个可以实现多种方法分类的软件，利用各个
对象的属性。决策树，距离、密度等-Weka is a collection of machine learning al gorithms for data mining tasks. The algorithms can either be applied directly to a dataset or ca lled from your own Java code. Weka contains tool 's for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for d eveloping new machine learning schemes. can be a real Categories are various methods of software, using all the attributes of objects. Decision Tree, distance, density, etc. Platform: |
Size: 15446016 |
Author:马何坛 |
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Description: 决策树 C4.5 分类器, 用C语言写的.大家一起参考一下. -C4.5 decision tree classifier, using the C language. U.S. with reference. Platform: |
Size: 143360 |
Author:sj2ac |
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Description: 实现决策树分类训练试验。
源自c4.5，在windows下用C++实现,简洁好用。用户只需要构建好特征说明文件，并选择一些参数既可以进行试验。-Realize decision tree classifier trained pilot. From c4.5, in windows using C++ Realize, concise easy to use. Users only need to build a good feature of the documentation, and select some of the parameters can be tested. Platform: |
Size: 139264 |
Author:胡伟湘 |
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Description: 该代码是数据挖掘里面的决策树算法 利用c45理论，通过对训练数据的分析判断，计算出各个数据的其它对目标属性的重要程度，即计算出每个其它数据的信息增益值来将训练数据逐步分类，最后得出目标分类，从而实现决策树的生成过程。最后即可利用此决策树来对新的数据进行测试，判断其目标属性的可能值。-The code is a data mining using decision tree algorithm inside the C45 theory, through the analysis of training data to calculate all the other data attributes on the target level of importance, that is, every other data to calculate the information gain value of the training data Category gradually came to the conclusion that the target classification, in order to realize the process of decision tree generation. Finally you can use this decision tree to test the new data to determine its target attributes possible values. Platform: |
Size: 769024 |
Author:zkm |
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Description: ID3决策树算法的JAVA实现：ID3算法是机器学习中的一种分类方法，本例子用java构建多叉树来实现id3算法。-ID3 Decision Tree Algorithm JAVA realize: ID3 machine learning algorithm is a classification method, the example of using java to build a multi-tree algorithm id3 realize. Platform: |
Size: 460800 |
Author:more |
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Description: 用java 语言编写的人工智能中的决策树演示-Using java language of artificial intelligence in the decision tree presentation Platform: |
Size: 418816 |
Author:杨柳 |
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Description: 决策树 C4.5 分类器, 用java语言写的.大家一起参考一下. -C4.5 decision tree classifier, using the java language. U.S. with reference. Platform: |
Size: 2048 |
Author:Kevinchen |
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Description: ID3 Decision Tree Algorithm JAVA realize: ID3 machine learning algorithm is a classification method, the example of using java to build a multi-tree algorithm id3 realize. Platform: |
Size: 460800 |
Author:thedarknesswarrior |
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Description: 采用Java实现的ID3决策树算法，基本实现了原理，支持分类，只支持标称型变量。-Java implementation using ID3 decision tree algorithm, the basic realization of the principle, support the classification, only support a nominal variable. Platform: |
Size: 5120 |
Author:iihaozl |
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Description: 使用纯JAVA语言原生开发C4.5决策树算法，没有使用工具包，并且通过界面展示了生成的决策树图像。-Using pure JAVA language Native Development C4.5 decision tree algorithm, do not use the toolkit, and by interface shows the image generated by the decision tree. Platform: |
Size: 1831936 |
Author:zk |
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Description: 利用决策树训练训练器 分辨 有毒蘑菇和无毒蘑菇 java书写，包含训练集及说明 代码无bug(Using decision tree training trainer to distinguish poisonous mushroom and non-toxic mushroom Java writing, including training set and explanation code.) Platform: |
Size: 38912 |
Author:西书城店
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