搜索资源列表
pattern-recognition-simulation
- 用mushrooms数据对模式识别课程讲述的各种模式分类方法[线性分类，Bayesian分类，Parzen窗，KNN]和特征选择和降维方法[PCA,LDA]进行了模拟，并给出了各类分类方法的结果，-It s the simulations about linear classification ,Bayesian ,Parzen and KNN of pattern recognition .And ,It gives the results.
MPCALDA
- 编程是由pca和lda结合的脸部特征提取，用于三维图像。-multilinear principal component analysis combined with Linear discriminant analysis 3D face feature extraction.
PCA-and-LDA-draw
- PCA和LDA的研究,我写了很久才做出来的，希望对大家有用，尤其是用在毕业设计上-A very useful tool to analysis PCA and LDA
PCAPLDA
- 这个程序是做课程设计用的，希望对有需要的同学进行有帮助，PCA+LDA经典人脸识别算法，先用PCA降维，再用LCA降维-This procedure is done with the course design, and I hope there is a need for students to help, PCA+LDA classical face recognition algorithms, first PCA dimension reduction, reuse LCA dimens
LDPCCODE
- 这个程序是在国外的网站下载，希望对有需要的同学有用，PCA+LDA经典人脸识别算法，先用PCA降维，再用LCA降维-This program is downloaded from the website in a foreign country, I hope to needy students useful, PCA+LDA classical face recognition algorithms, first PCA dimension reduction, reuse LCA dimen
PCA-and-LDA-Face-recognition
- 运用PCA和LDA进行人脸识别的MATLAB代码 -do the face recognition use the principal component analysis and linear discriminant analysis
PCAPLDA
- PCA+LDA人脸识别，PCA降维到N-C,（N为训练样本数，C为类别数）使得Sw非奇异，主要是解决小样本，数据集为ORL，每类取9（可改）个图片-PCA+LDA recognition, PCA dimensionality reduction to NC, (N is the number of training samples, C is the number of categories) make Sw nonsingular, mainly to resolve the small s
PCAPLDA
- 一个很好的LDA算法 包括数据预处理 会在数据比较dirty的情况下 先进行PCA 然后LDA-A good LDA algorithm including data preprocessing data comparison in the case of the first dirty conduct PCA and LDA
LDAgdm
- 详细说明:使用matlab实现的LDA(线性判别分析)分类器,以及PCA的实现-matlab implementation of the LDA algorithm and the realization of the linear Discriminant Analysis
pca-lda
- PCA、LDA特征提取源代码以及相应使用数据-PCA, LDA source code and data
LLE
- lle降维，可以参考非线性降维的方法，感觉没lda好用，比pca还行(LLE dimension reduction)
drtoolbox
- 包含多种常用维数优化算法及应用，PCA , ICA, LDA，LFA LPP，KPCA 等等。(There are many Dimensionality Reduction methods including PCA , ICA, KICA and so on.)
pca-lda
- 主成分分析法和线性判别分析常用来对原始数据进行简单的数学分析(Principal component analysis and linear discriminant analysis are usually used for simple mathematical analysis of raw data.)