搜索资源列表
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基于粗糙集理论和BP神经网络的分层递阶分类算法。-based on rough set theory and neural networks hierarchical classification algorithm.
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一种基于组合变换的粗糙集属性约简算法，从数据库中下载的毕业论文哦-Combined transformation based on rough set attribute reduction algorithm, thesis downloaded from the database, oh
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粗糙集属性约简算法的代码，数据库中下载的算法-Rough set attribute reduction algorithm of the code, database, download the algorithm
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基于遗传算法的粗糙集属性约简。数据库使用的是ACCESSS数据库，编程环境VS2008。，
-Genetic Algorithm-based rough set attribute reduction. Database the use ACCESSS database programming environment VS2008. ,
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将core.txt文件放在C盘根目录下,然后打开matlab，点击“文件”-“打开”选中main.m文件，“运行”这个文件。
命令窗口马上就会显示出运行结果。
mm_Red.m为封装的盲目约简算法.返回值为约简结果.
sxzyd_Red为封装的基于属性重要度约简算法.返回值为约简结果.
bsjz_Red为封装的辨识矩阵约简算法.返回值为辨识矩阵和约简结果.
cal_sig为封装的求属性重要度的函数。
max_min为封装的求属性度最大，划分个数
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matlab粗糙集算法，主要使用于神经网络和支持向量机等算法的预处理，可以有效地筛选数据-matlab rough set algorithm, mainly used in the pre-processing of the neural network and support vector machine algorithm can effectively filter the data
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涵盖目前识别和智能计算的理论和方法，包括支持向量机，神经网络，决策树，粗糙集理论，模糊集理论，和遗传算法-Covers the recognition and intelligent computing theory and methods, including support vector machines, neural networks, decision trees, rough set theory, fuzzy set theory and genetic algorithm
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可以实现粗糙集的整个算法，从上下近似、属性约简、属性重要度到决策规则的输出和规则的确定性因子，全部实现。内附测试数据，有详细的注解，可以实现与数据库的直接连接。-Rough set can be achieved throughout the algorithm, from top to bottom approximation, attribute reduction, attribute importance to the uncertainty factor output of decis
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基于遗传算法的粗糙集条件属性约简算法，运算效率较高。-The algorithm of rough set reduction based on genetic algorithm，with high efficiency.
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一种利用粗糙集理论的知识约简算法，MATLAB实现-A knowledge reduction algorithm using rough set theory, MATLAB realization
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邻域粗糙集属性约简程序，约简方法为胡清华的前向贪心算法，包含求正域，属性重要度计算及最后约简出的重要属性。-Neighborhood rough set attribute reduction program, before the reduction method for qing-hua hu to the greedy algorithm, contains positive region, calculation and the reduction of attribute import
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Rough set of matlab code, which contains several files
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The discretization of attribute reduction of rough set and the method of rule extraction are described
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