Description: 一个基于ID3方法的具体实例，其中的ID3use包括一个完整的建立决策树的模型。-ID3 method based on a specific examples, the ID3use including the establishment of a complete decision tree model. Platform: |
Size: 225280 |
Author:张召 |
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Description: C4.5是决策树的经典算法
C4.5 归纳学习是完全自动的学
习算法，所需要做的是选取有用的特征，构建实例数据库供它学习-C4.5 decision tree is the classic C4.5 inductive learning algorithm is completely automatic learning algorithm, what needs to be done is to select useful features, build databases for its examples of learning Platform: |
Size: 1024 |
Author:唐宇 |
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Description: id3算法进行决策树生成 以信息增益最大的属性作为分类属性，生成决策树，从而得出决策规则。id3的源码决策树最全面最经典的版本.id3决策树的实现及其测试数据.id3 一个有用的数据挖掘算法，想必对大家会有所帮助！-id3 decision tree algorithms to generate information gain the greatest attribute as a classification attributes, generate decision tree, Thus, it reached a decision-making rules. Id3 the most comprehensive source Decision Tree classic version. Id3 decision tree and the achievement test data. Id3 1 useful data mining algorithms, surely they will help you! Platform: |
Size: 38912 |
Author:李顺古 |
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Description: id3的源码决策树最全面最经典的版本.id3决策树的实现及其测试数据.id3 一个有用的数据挖掘算法，想必对大家会有所帮助！id3算法进行决策树生成 以信息增益最大的属性作为分类属性，生成决策树，从而得出决策规则。-id3 the most comprehensive source Decision Tree classic version. Id3 decision tree and the achievement test data. I d3 a useful data mining algorithms, surely they will help you! Id3 decision tree algorithms to generate information gain the greatest attribute as a classification attributes, generate decision tree, Thus, it reached a decision-making rules. Platform: |
Size: 39936 |
Author:王小明 |
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Description: 使用C#实现的决策树算法实例，对初学者有很大的帮助-The use of C# Realize the decision tree algorithm examples of great help for beginners Platform: |
Size: 76800 |
Author:杨羽 |
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Description: 基于决策树和贝叶斯的预测分析器，可以对数据库中的数据集通过训练学习后根据训练结果进行信息预测。-Based on Decision Tree and Bayesian prediction of the analyzer can be in the database data sets through training to learn the results after the training information in accordance with prediction. Platform: |
Size: 3811328 |
Author:季芳 |
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Description: The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported. Platform: |
Size: 4096 |
Author:Minh |
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Description: 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. Platform: |
Size: 27648 |
Author:EMMILY |
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Description: This my implementation of ID3 algorithm. The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported. -This is my implementation of ID3 algorithm. The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported. Platform: |
Size: 62464 |
Author:Putra |
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