搜索资源列表
pca-face-recog
- 使用经典方法主成分分析方法进行人脸识别，识别效果好-failed to translate
PCA
- PCA算法实现，对一组数据进行主成分分析。文件中提供的CMyPCA.cpp文件实现了PCA算法，并在工程文件中通过举例说明了算法的使用方法。-PCA algorithm, principal component analysis of a set of data. Provided in the document CMyPCA.cpp files PCA algorithm, and illustrates the use of the algorithm adopted in the proj
PCA
- 该源码使用主成分分析对原数据点进行分析。-Reshape the data points using the principal component analysis
pca-svm
- 主成分分析，支持向量机介绍，PDF文档，自制-Principal component analysis, support vector machine, PDF documents, homemade
PCA-jacobi
- 使用C#对对数据进行主成分分析，并得出结果。-Principal component calculation in C#.
Face-recognition-based-PCA
- 基于主成分分析的人脸识别系统，用matlab写的-Written based on principal component analysis of face recognition system using matlab
PCA
- 运用主成分分析PCA的方法，实现人脸的重建-Based on principal component analysis PCA face reconstruction
PCA
- 主成分分析PCA源代码（C++，matlab）主成分分析PCA源代码（C++，matlab）-Principal Component Analysis PCA source code (C++, Matlab), principal component analysis PCA source code (C++, Matlab)
PCA
- PCA是主成分分析，能够在众多的因素中找出重要的影响条件，并分析PCA的贡献率-PCA is the principal component analysis to identify important impact in a number of factors, and analyze the contribution rate of the PCA
Face-recognition-using-pca
- 使用主成分分析进行人脸图像的识别，并计算识别率-Using principal component analysis for face image recognition, and calculate the recognition rate
PCA
- 应用主成分分析的方法实现数据降维，主成分个数通过累积方差贡献率的方法来确定-The principal component analysis of data dimensionality reduction, the number of principal components to determine the cumulative variance contribution rate
face-recognition-based-on-pca
- 基于主成分分析的人脸识别，用主成分分析提前特征，用模版匹配进行分类-face recognition based on PCA
PCA_MATLAB
- PCA(主成分分析)的MATLAB源代码，包含测试例子及使用文档，该算法主要用于图像分类时特征的降维。-PCA (Principal Component Analysis) of the MATLAB source code, including test case and use the document, the algorithm is mainly used for image classification and feature dimensionality reduction.
Ppca_face_recc
- 基于pca主成分分析实现人脸识别功能，是人脸识别中比较较经典的算法之一，取得很好的效果，已通过测试。 -Pca-based principal component analysis of face recognition feature is face recognition than the classic algorithm achieved very good results, has been tested.
PPPCCALDAC
- PCA(主成分分析法)、LDA(线性判别法)两种方法是主要的的线性降维法，有非常好的效果，希望对大家能够有用！ 已通过测试。 -PCA (Principal Component Analysis), LDA (linear discriminant method) two methods are the main linear dimensionality reduction method, with very good results, we hope to be useful! Has
PCA
- 主成分分析(Principal Component Analysis, 简称PCA)是一种常用的基于变量协方差矩阵对信息进行处理、压缩和抽提的有效方法。 -The principal component analysis (Principal Component Analysis, PCA) is a common covariance matrix of information processing, compression and extraction.
pca
- 主成分分析是设法将原来众多具有一定相关性（比如P个指标），重新组合成一组新的互相无关的综合指标来代替原来的指标。-Principal Component Analysis，PCA
pca
- 主成分分析 pca函数代码，用于数据的降维、压缩、去噪、主成分分析等方面-principal component analysis
PCA
- 在多变量统计中，数据有很强的相关性，对数据进行主成分分析，这样可以避免过拟合- Multivariate statistical data there is a strong correlation, principal component analysis of the data, and to avoid over-fitting
PCA-Matlab-CODE
- 主成分分析源代码，有详细说明，中文详细说明-Principal Component Analysis Matlab CODE