搜索资源列表
用PCA（非工具包，自写）实现LDA
- 上了一门统计分析的课程，所有课程所学内容均不允许使用工具包，特自写PCA，实现LDA线性分类，希望可以与大家分享，一起学习参考，
PCA-Python
- 用Python语言实现PCA(Principle Component Analysis)。-PCA with python.
pca
- 利用OpenCV库函数实现PCA（主成成分分析）算法，该算法是经典人脸识别算法Eigenface里的核心算法。-Use OpenCV library functions achieve PCA (Principal Component Analysis into) algorithm, which is a classic face recognition algorithm Eigenface in core algorithm.
pca
- 使用MATLAB实现主成分分析，其中包含两种不同的方法。(Two different methods are used to achieve principal component analysis by MATLAB.)
pca
- 主成分分析法的c++代码，有俩个版本的实现方法(C++ code of principal component analysis)
PCA
- PCA LDA实现，根据累积贡献率确定主成分个数(PCA LDA MATLAB The number of principal components is determined according to the cumulative contribution rate)
pca
- 主成分分析实现代码，以测试集辛烷值含量预测结果对比为例，内附数据，代码，matlab实现(Principal component analysis implementation code)
PCA
- PCA算法的matlab实现及算例，包含原始数据(matlab code of PCA in machine learning)
pca
- 主成份分析代码，实现对信号的主成分分析和实现，有利于更好理解这部分功能。(Principal component analysis code, to achieve the main component of the signal analysis and implementation, is conducive to a better understanding of this part of the function)
PCA-mefhods
- 采用各种不同的方法实现PCA,包括truePCA,empca等,不错的(PCA is realized by using various methods, including truePCA, empca etc., good)
gabor-pca
- 用gabor结合pca降维实现人脸识别，能得到较好的识别率(face recognition through gabor-pca)
PCA
- 该程序可以实现数据的主成分提取，以及相关系数矩阵，得分矩阵，还有T^2统计量，可视化效果好。(The program can achieve the main component extraction of data, as well as correlation coefficient matrix, scoring matrix, as well as T^2 statistics, visual effect is good.)
NMFs算法用于实现基于人脸局部特征的人脸识别
- 实现了人脸检测和识别算法，很好的定位人脸位置(can efficiently locate the face in image.)
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.)
pca
- 实现一个简单的PCA降维与重构程序，用到的数据在.txt文件中。还有用于测试的.m文件(To achieve a simple PCA dimension reduction and reconstruction procedures)
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,
119128653pca
- 用java编写的部分PCA程序，有错误请指出(Some PCA programs written with Java, error, please point out)
PCA_FaceRecognition
- 使用MATLAB代码实现PCA人脸识别，配套图片使用(The use of MATLAB code to achieve PCA face recognition, supporting the use of pictures)
PCA
- MATLAB实现主元分析法，实现数据的压缩，提取主元(MATLAB realize Principal Component Analysis, To achieve data compression, extract the principal component)
]ORL+PCA+SVM-11
- 编写了用户界面程序实现ocr人脸数据集的识别，使用了svm分类器(A user interface program is developed to realize the recognition of OCR face data set, and the SVM classifier is used)