Description: C语言设计案例源代码,算法等等C语言设计案例源代码,算法-C language source code case design, algorithm, etc. C language source code case design, algorithm, etc. Platform: |
Size: 2934 |
Author:唐爱六 |
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Description: 这是决策树C4.5算法的java版源码。希望大家能喜欢,愿共同分享!-Decision Tree Algorithm C4.5 java version of the source code. Hope you will like it is willing to share! Platform: |
Size: 1729 |
Author:gosiger |
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Description: 这是决策树C4.5算法的java版源码。希望大家能喜欢,愿共同分享!-Decision Tree Algorithm C4.5 java version of the source code. Hope you will like it is willing to share! Platform: |
Size: 1024 |
Author:gosiger |
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Description: 数据挖掘课中的一个算法c4.5决策树源码,只要有相应的测试文件就可以了-Data mining courses in a decision tree algorithm c4.5 source code, as long as the corresponding test file on it Platform: |
Size: 140288 |
Author:王俊杰 |
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Description: C4.5算法源码,c4.5是ID3算法的改进,本资料十分全,希望对大家有帮助-C4.5 algorithm source code, c4.5 ID3 algorithm is improved, the information is very full, we want to help Platform: |
Size: 1024 |
Author:二毛 |
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Description: matlab源代码 C4.5算法 经典算法
这里有具体的操作 是为.M文件
-C4.5 algorithm matlab source code there is the classical algorithm for the specific operation. M files Platform: |
Size: 5120 |
Author:joyna |
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Description: 该源代码主要实现C4.5决策树算法,C4.5是对ID3算法的一种改进,它完善了ID3算法,补充了其算法的一点不足-The source code is the main achievement of C4.5 decision tree algorithm, C4.5 is an improved ID3 algorithm, which improved the ID3 algorithm, the algorithm added a little less than its Platform: |
Size: 15360 |
Author:小强 |
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Description: 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. C4.5算法继承了ID3算法的优点,并在以下几方面对ID3算法进行了改进:
1) 用信息增益率来选择属性,克服了用信息增益选择属性时偏向选择取值多的属性的不足;
2) 在树构造过程中进行剪枝;
3) 能够完成对连续属性的离散化处理;
4) 能够对不完整数据进行处理。
C4.5算法有如下优点:产生的分类规则易于理解,准确率较高。其缺点是:在构造树的过程中,需要对数据集进行多次的顺序扫描和排序,因而导致算法的低效。-The design and implementation of C4.5 and source code,C4.5 algorithm is a classification of the decision tree algorithm of machine learning algorithms, the ID3 algorithm is the core algorithm. Platform: |
Size: 2048 |
Author:李菲 |
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Description: C4.5 algorithm implementation source code, developed by Ross Quinlain which classifies data, using decision trees. Platform: |
Size: 5120 |
Author:sopotica |
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