搜索资源列表
mani.rar
- 一个集成了8种降维方法的GUI（包括常见的PCA、LLE、isomap、HLLE等线性与非线性将为方法）,An integrated eight kinds of dimensionality reduction methods GUI (including common PCA, LLE, isomap, HLLE, etc. will be linear and nonlinear methods)
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.
PCA-dimensionalityreduction
- 跟数据降维有关的matlab 源码 看清题目选择源码-dimensionality reduction of matlab code
pcaceshi
- 颜色特征HSV模型，用pca降维，已经测试成功-pca dimensionality reduction
PCA
- PCA算法实现对多维数据进行降维，内涵exel数据可供检验-PCA algorithm to achieve dimensionality reduction of multidimensional data, connotation exel data available for inspection
PCA
- 主元分析是对数据进行平移和旋转变换，提取几个比较重要的变量来表示原始空间中的重要信息，实现对数据的降维-Principal component analysis for data translation and rotation transformation to extract a few of the more important variables to represent the important information in the original space, to achiev
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
- 主成分分析（Principal Copmponent Analysis，简称PCA）是一种常用的机遇变量协方差矩阵对信息进行处理、压缩和提取的有效方法。主成分分析，这种方法可以有效的找出数据中最“主要”的元素和结构，去除噪音和冗余，将原有的复杂数据降维，能够发掘出隐藏在复杂数据背后的简单结构。-PCA (Principal Copmponent Analysis, abbreviated PCA) is a commonly used covariance matrix Opportunity
pca
- pca降维，实现机器学习中的降维。 pca降维，实现机器学习中的降维。 pca降维，实现机器学习中的降维。 pca降维，实现机器学习中的降维。-Descr iption of PCA, realizing the PCA code
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)
pca
- pca是主成分分析，提取特征，对数据进行降维处理(PCA is principal component analysis, which extracts features and processes the data in reduced dimension)
PCAjiangwei
- Gabor提取人脸图像特征后，PCA进行降低维数，(After Gabor extracts image features, PCA reduces dimensionality)
PCA-ICA
- 实现了主元分析（PCA）和独立分量分析（ICA）相关信号处理。非线性降维。(Implements Principal Component Analysis (PCA) and Independent Component Analysis (ICA) correlation signal. Non-linear dimension reduction using kernel PCA.)
gpldecha-e-pca-d542a9b
- PCA是一种非线性降维方法特别适合于概率分布，得到了指数族PCA的POMDPs压缩。(Matlab implementation of E-PCA which is a non-linear dimensionality reduction method particularly suited for probability distributions, see the paper Exponential Family PCA for Belief Compression in POMDPs.)
PCA实现特征降维
- pca和_fase_pca实现特征降维，两种算法都有所改进，特别是pca可以根据自己的需要进行相应的改进，代码清晰易懂，希望对你有帮助。(PCA and _fase_pca to achieve feature reduction, the two algorithms have improved, especially PCA can be improved according to their needs, the code is clear and easy to understand,
PCA
- 用matlab自带的PCA算法对图像进行降维(Dimensionality reduction for images)
pca
- 大数据降维方法，具体的处理了图像等，包括数据的冗余部分，利用PCA技术快速降维。(Large data dimensionality reduction method.Specifically dealing with images, including redundant parts of data, and using PCA technology to reduce dimensionality rapidly.)
PCA,KPCA完整程序
- 降维，用作聚类算法使用。具有很好效果，可以用作图像去噪(Dimensionality reduction is used as a clustering algorithm. It has good effect and can be used for image denoising.)
pca
- 应用于数据降维的一种MATLAB程序，可以实现从高维到低维的降解(A matlab program applied to data dimensionality reduction can realize the degradation from high dimension to low dimension)