Search - feature selection rough set

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[matlab] NRS_FW_FS DL : 0: Neighborhood rough set based heterogeneous feature subset selection
Update : 2025-03-07 Size : 1kb Publisher : sam
[Mathimatics-Numerical algorithms] rsar_1.3.3.tar DL : 0: sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper: Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000. rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset. Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts. -sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper: Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000. rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset. Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts.
Update : 2025-03-07 Size : 713kb Publisher : NH
[Mathimatics-Numerical algorithms] Matlabcode DL : 0: 粗糙集代码 data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection -Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection
Update : 2025-03-07 Size : 38kb Publisher : gq
[matlab] RSAttributeReduction DL : 0: 基于粗糙集的特征子集筛选的一种算法-Based on rough set feature subset selection of an algorithm! ! !
Update : 2025-03-07 Size : 1kb Publisher : 沈沛鼎
[Other] kernelizedfuzzy DL : 0: kernelized fuzzy rough set based feature evaluation selection
Update : 2025-03-07 Size : 3kb Publisher : HOU
[Mathimatics-Numerical algorithms] method DL : 0: method粗糙集的地面目标识别特征量选取方法-Rough set the amount of artillery ground target recognition feature selection method
Update : 2025-03-07 Size : 449kb Publisher : QQ
[matlab] 222222111 DL : 0: fuzzy preference rough set based feature evaluation and selection
Update : 2025-03-07 Size : 6kb Publisher : dw
[matlab] 44444444 DL : 0: kernelized fuzzy rough set based feature evaluation selection
Update : 2025-03-07 Size : 5kb Publisher : dw
[matlab] Rough-Set-Attribute-Reduction DL : 0: 基于粗糙集的特征选择Matlab源程序。-Feature selection based on rough set.
Update : 2025-03-07 Size : 2.22mb Publisher : 肖进
[AI-NN-PR] test DL : 0: 引入能直接处理连续型数据的邻域粗糙集约简模型，给出一种基于邻域粗糙集模型和粒子群优化的特征选择算法。仿真实验结果表明该算法可以选择较少的特征，改善分类的能力。-employs the neighborhood rough set reduction model which can process the numerical features directly without discretization. Then the particle fitness function in particle swarm optimization (PSO) algorithm is built based on that model. Finally, a novel feature selection algorithm based on particle swarm optimization and neighborhood rough set reduction model is proposed. Experimental results prove that the new algorithm improves classification ability with fewer features selected.
Update : 2025-03-07 Size : 16kb Publisher : 伍洁
[AI-NN-PR] QuickSortOrderReduct DL : 0: 引入能直接处理连续型数据的邻域粗糙集约简模型，给出一种基于邻域粗糙集模型和粒子群优化的特征选择算法-Introduce neighborhood rough set reduction model can deal directly with continuous data, given the feature selection algorithm based on neighborhood rough set model and particle swarm optimization
Update : 2025-03-07 Size : 13kb Publisher : 伍洁
[AI-NN-PR] Rough-Set-based-Feature-Selection DL : 0: 离散人工蜂群算法用于解决特征选取问题，可以学习文章中将群智能算法离散化的方法，以便于解决离散问题。-Discrete artificial bee colony algorithm for solving feature selection problem, you can learn article will swarm intelligence algorithm discretization method, in order to solve the discrete problem.
Update : 2025-03-07 Size : 862kb Publisher : 丁毅
[Internet-Network] feature-selection113 DL : 0: 粗糙集；特征选择；核属性；不可分辨关系；依赖度；-rough set ；feature selection；Nuclear properties；indiscernibility relation；dependence
Update : 2025-03-07 Size : 13kb Publisher : 张洋