搜索资源列表
Feature&Selectio
- mapx的Feature和Selection示例程序-MapX and the Feature Selection sample program
LDA
- 线性判别分析（LDA）用于特征选择，可以对数据集或者图像提取有用特征，用于分类或者聚类等机器学习应用中-Linear Discriminant Analysis (LDA) for feature selection, application in dataset or image feature extraction, for classification or clustering applications in machine learning
fsbox
- Stepwise forward and backward selection of variables using linear models
NRS_FW_FS
- Neighborhood rough set based heterogeneous feature subset selection
25
- 关于rbf神经网络实现图像分类的优化算法英文文献 源于著名期刊I-Hyperspectral Feature Selection and Classification
rsar_1.3.3.tar
- 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 Fu
Matlabcode
- 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 bas
Text_Feature_Extraction
- 文本特征提取方法研究。文本的表示及其特征项的选取是文本挖掘、信息检索的一个基本问题，它把从文本中抽取出的特征词进行量化来表示文本信息。-Text Feature Extraction. And characteristics of the text of that item selection is text mining, information retrieval is a basic problem, which to extract from the text to quantify t
RSAttributeReduction
- 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! ! !
kernelizedfuzzy
- kernelized fuzzy rough set based feature evaluation selection
matlab 蚁群算法ACO_feature_selection
- 蚁群算法用与特征选择，针对传统蚁群聚类算法收敛速度过慢的问题，提出一种对蚁群算法进行改进的聚类算法。而数据的高维使数据具有稀疏、不可聚集等特性，使聚类算法实验效果精度低和耗时大，将邻域特征选择与聚类算法结合，提出了一种蚁群聚类优化的邻域特征选择算法(Ant colony algorithm and feature selection)
FSelector_0.21.tar
- feature selection using F selector code
fhgkj-master
- The matlab code mRMR use for feature selection
58095
- feature selection for matlab
bootstrap-datepicker-1.6.4-dist
- feature selection for matlab2
feature-selection-master
- 最小冗余最大相关性（MRMR）（MRMR.M） 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘（PLS）回归系数（ReGCOEF.m） 使用MATLAB统计工具箱中的PLSReress ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.） 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA
BSOFS
- 改进的头脑风暴算法（MBSO）用于特征选择，MBSO方法文章来源：Zhan, Zhi Hui, et al. "A modified brain storm optimization." Evolutionary Computation IEEE, 2012:1-8.(Improved brainstorming algorithm for feature selection, MBSO method source: Zhan, Zhi Hui, et al. "A
BPSO for feature selection
- 二进制粒子群算法（Binary particle swarm optimization algorithm，BPSO）解决特征选择问题。(Binary particle swarm optimization algorithm for feature selection problem)
feature-selection-mRMR-master
- 特征选择方法，用于降低数据维数，常见的一种特征筛选手段，可以从大量变量中筛选特征变量实现保留变量与目标之间的最大相关性(feature selection method for mRMR)
Feature Selection using GA
- 用二进制遗传算法做特征选择，此算法效率高，选择的特征数目少。(The binary genetic algorithm is used for feature selection, which has high efficiency and few features.)