搜索资源列表
KPCA.rar
- 一个很好的PCA程序。它可用于数据的降维，消噪及特征提取。,A good PCA procedures. It can be used for data dimensionality reduction, de-noising and feature extraction.
FastICA_25
- 独立分量分析的算法，用于分离出独立分量，用于图像降维，特征提取-Independent component analysis algorithms, used to separate out the independent component for the image dimensionality reduction, feature extraction
clsf_dpd_fast
- Neighborhood rough set based feature evaluation and reduction
daima
- （压缩包里一共有5个代码） pca+lda+粗糙集+模糊神经网络 saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat 1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat 2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat
eigenvalue_computation.tar
- 快速PCA计算方法，有效实现降维等操作，和特征选择-Fast PCA method of calculation of effective dimension reduction and other operations, and feature selection
ica_appD_demo
- 高校的ICA计算代码，广泛用于特征选择，降维，目标识别等-Colleges and universities ICA calculation code, widely used in feature selection, dimensionality reduction, target identification, etc.
SVM
- In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is in
HIGH_DIMENSIONAL_FEATURE
- HIGH DIMENSIONAL FEATURE REDUCTION VIA PROJECTION PURSUIT
CCA_zq
- 用于特征降维，特征融合，相关分析等多元数据分析的典型相关分析Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis, canonical correlation analysis of Matlab code implementation.
DCCA_zq
- 用于特征降维，特征融合，相关分析等多元数据分析的鉴别型典型相关分析（DCCA）Matlab代码实现。-For feature reduction, feature fusion, multivariate data analysis and correlation analysis based identification of canonical correlation analysis (DCCA) Matlab code implementation.
GCCA_zq
- 用于特征降维，特征融合，相关分析等多元数据分析的广义典型相关分析（GCCA）Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis using generalized canonical correlation analysis (GCCA) Matlab code implementation.
LDA_zq
- 用于特征降维，特征融合，相关分析等多元数据分析的fisher鉴别分析（FLDA）Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis of the fisher discriminant analysis (FLDA) Matlab code implementation.
PCADR
- 用于特征降维人脸识别等多元数据分析的主分量分析投影的Matlab代码实现。-For feature reduction and other multivariate data analysis, face recognition principal component analysis projection of the Matlab code implementation.
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
pcaexpressprot
- We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality red
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
featurereductionmethods
- 这是一些收集到的线性和非线性的特征提取的算法，挺多也挺好的-these algorithms are very useful for feature reduction
empca
- PCA特征降维，用于图像处理人脸识别等模式识别领域和数据挖掘两领域-PCA feature reduction, image processing for face recognition and other pattern recognition and data mining of two areas
jiangwei
- 高维数据特征降维综述，电子书格式，欢迎下载-High-dimensional data feature reduction review, e-book format, please download ~ ~ ~ ~
progarmlab4
- The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing A common problem in statistical pattern recognition is feature selection or feature extraction. Feature selec