搜索资源列表
通过不同方法进行粗糙集属性约简matlab完整程序
- 通过不同方法进行粗糙集属性约简matlab完整程序，便于进行对比,By different methods of rough set attribute reduction matlab a complete program, to facilitate comparison
Roughset.rar
- 这是利用粗糙集理论做得最小值约简法代码,值得借鉴,This is the use of rough set theory has done the minimum code Reduction Act, it is worth drawing
Fast attributer eduction
- 粗糙集理论属性约简的例子，基于MATLAB实现,This is the use of rough set theory
rsreductwithattributes.rar
- 信息系统的盲目删除属性约简算法，采用matlab实现,Information system blindly delete attribute reduction algorithm implementation using matlab
rosetta
- 粗糙集工具箱 可以进行粗糙集上下近似集的计算，重要度等等 属性约简 决策分类-Toolbox rough sets rough sets can calculate the upper and lower approximations, importance, etc., etc. Classification Decision Attribute Reduction
rsda(Matlab)
- 粗糙集属性约简过程中的下近似及上近似域的matlab实现-Rough set attribute reduction process under the domain of approximate and matlab
main
- KDD99的属性约简，国外高人写的代码。-KDD99 of attribute reduction, foreign Gaoren to write code.
roughsetCprograms
- 用c语言编的基于粗糙集理论的属性约简程序-Using c language series based on rough set theory attribute reduction procedures
Reduction
- 基于Pawlak属性重要度的属性约简算法，包含论文算法及C++源代码。-Attribute importance based on Pawlak' s attribute reduction algorithm, including papers algorithm and C++ source code.
roughset
- 粗糙集matlab算法，有属性约简，值约简，规则生成等多种算法。-Neighborhood rough set based feature evaluation and reduction
ReductofRoughSetMatlab
- 利用Matlab实现决策系统的属性约简，完整源代码Word文档-Using Matlab to achieve decision-making system attribute reduction, complete source code Word document
roughsetattributioncut
- 粗糙集约简的matlab算法,包含了基本的约简算法-Rough Set Theory and matlab algorithm, including the basic reduction algorithm
rs
- 粗糙集(Roug Set)属性约简源代码(C/C++实现) -Rough Sets (Roug Set) attribute reduction source code (C/C++ implementation)
200851212344894641
- 属性约简程序，对程序员很有帮助，欢迎大家下载-err
RS reducta priori regression
- 基于粗糙集的知识约简算法和采用回归进行的知识约简表示-Based on Rough Set Knowledge Reduction Algorithm and the use of regression express the knowledge reduction
rstPawlak
- REDUCT_PAWLAK 基于Pawlak属性重要度的属性约简算法-Key property REDUCT_PAWLAK based on Pawlak Attribute Reduction Algorithm
Anewalgorithmofattributereductionbasedondiscernibl
- 一种改进的基于区分矩阵的属性约简算法，粗糙集理论研究-A new algorithm of attribute reduction based on discernibly matrix
一种基于MapReduce的粗糙集并行属性约简算法
- 云计算技术是海量数据挖掘的一种高效解决方案，将MapＲeduce 并行计算模型与粗糙集属性约简算法相结合，提出一种基于MapＲeduce 的浓缩布尔矩阵并行属性约简算法。该算法提高了粗糙集属性约简算法对大数据的处理能力和效率，并能适应云计算环境。实验结果表明，所提算法具有良好的效率、加速比和可扩展性。(Cloud computing technology is a high efficient solution for massive data mining.)
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
粗糙集实验--属性约简
- 可以进行属性约简以达到降维的目的(Attribute reduction can be carried out to achieve dimensionality reduction)