搜索资源列表
LDA
- LDA 的matlab源码实现，Jonathan Huang编写的，是目前唯一可用于且正确的源码，可用于图像特征降维
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
PCA
- PCA,主成分分析，可应用于矩阵降维，人脸特征提取及人脸识别。-PCA, principal component analysis, can be applied to matrix reduction, facial feature extraction and face recognition.
pca
- 主成分分析程序,应用于图像特征提取，数据降维等方面 -the code of PCA
FunFDA
- FunFDA模式识别中特征提取中的数据降维的一种算法-fisher discriminant analysis
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
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.
KLFDA
- 基于局部Fisher准则的非线性核Fisher辨别分析，应用于有监督的特征提取与高维数据的有效降维。-Kernel Local Fisher Discriminant Analysis for Supervised Dimensionality 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 ~ ~ ~ ~
Eigenface
- 人脸特征降维，提取特征人脸，将像素空间映射到人脸空间，计算人脸特征向量，人脸识别-Facial feature reduction, feature extraction face, the pixel space is mapped into the face space and face feature vector computation, face recognition
fsvmPpca-face-Recognition
- 首先用PCA对ORA人脸图像降维，然后用模糊支持向量机对提取的特征向量进行分类，识别率较高。-First using PCA for dimensionality reduction ORA face image, and then use fuzzy support vector machine to classify the extracted feature vectors, the recognition rate is higher.
K-Means PCA降维
- K-Means算法,不要求建立模型之后对结果进行新的预测，没有相应的标签，只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the character
FastICA
- 独立成分分析matlab代码，进行特征降维与特征选择(ICA transform for feature selection)
KLT
- 本程序实现了利用KL变换进行特征分解，并进行降维重建，示例图片在文件中给出。(This program realizes feature decomposition using KL transform and dimensionality reduction reconstruction. The example pictures are given in the file.)