搜索资源列表
roughsets
- 过不同方法进行粗糙集属性约简matlab完整程序-rough set matlab program
best
- 该程序是粗糙集代码,里面对程序调试有说明,按照说明可以直接调试,实现约简,提取规则-The program is rough set code, which are described on the program debugging, follow the instructions can debug, to achieve reduction, extraction rules
ccj
- 几篇粗糙集的论文文献,感觉不错,跟大家分享-Papers several rough set literature, I feel good, to share with you
rst
- 基于粗糙集属性约简的算法,不错,可以-Rough set attribute reduction algorithm, a good
rsyujian
- 粗糙集的属性约简 离散化,规则提取的方法有说明-rough set reduce
2011
- 通过不同方法进行粗糙集属性约简matlab完整程序-Through different methods of rough set attribute reduction complete program matlab
RSTT-CODE
- 粗糙集理论的属性约简方法及应用研究,很有用的哈-Rough set attribute reduction method and application, very useful, ha! ! ! !
Rough-Set-Attribute-Reduction
- 基于粗糙集的特征选择Matlab源程序。-Feature selection based on rough set.
生成高斯粗糙面
- 生成高斯粗糙面,学习了好长时间才学会的,可以修改为自己想要的高斯粗糙面,改参数
matlab 3d高斯粗糙表面
- matlab生成3d高斯粗糙表面,将代码输入matlab命令行窗口运行即可
69491728rough-set-codes
- 胡清华邻域粗糙集源码,matlab源代码,方便可用(Hu Qinghua neighborhood rough sets source code, matlab source code, easy to use)
ifft
- 路面粗糙度模拟,利用逆傅里叶变换方法模拟粗糙度(road surface roughness)
KOF
- 粗糙集 进行 分类前计算,提供粗糙集计算结果 ,高效快速。(The rough sets are classified before the calculation, and the rough sets are provided. The results are efficient and fast.)
RSLibrary
- 粗糙集属性约简工具类,别人编写很不错,可以借鉴(rought set reduce utils , just for learn ,thank you)
表面粗糙度Ra的matlab计算程序
- 包含高斯滤波及最小二乘中线的详细计算过程,可计算自由表面粗糙度和一维粗糙度。
featureselect_FW_fast
- 粗糙集,属性简约,能够提供良好的测试,需要做一些参数及内容调整(Rough sets, attribute parsimony, can provide good testing and need to do some parameter and content tuning)
改进人工蜂群算法优化ELM分类模型_赵虎
- 经典的粗糙算法集代码,内有实例。主要用来数据约减,数据分类,优化(Classic rough sets of code, there are examples)
11290323Reduction
- 粗糙集是一种软计算方法,此程序是用来处理粗糙集约简,使约简更方便得出。(Rough set is a kind of soft computing method, which is used to deal with rough set reduction.)
MoM
- 使用矩量法求解了垂直极化下的粗糙面散射系数(The scattering coefficient of rough surface under vertical polarization is solved by the method of moments)
带权重条件熵的属性约简算法
- 粗糙集理论中最重要的内容之一就是属性约简问题,现有的许多属性约简算法往往是基于属性对分类的重要性,如果属性约简的结果能满足用户实际需要的信息,如成本、用户的偏好等,那么约简理论将会有更高的实用价值。基于此,从信息熵的角度定义了带权重的属性重要性,然后重新定义了基于带权重的属性重要性的熵约简算法。最后通过实际例子说明,与基于属性重要性的熵约简算法相比,考虑权重的算法更加符合用户的实际需求。(Attribute reduction is one of the most important conte