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主成分分析（PCA)算法是用于简化数据的一种技术,对于某些复杂数据就可应用主成分分析法对其进行简化。-principal component analysis (PCA) algorithm is used to simplify the technology of data, For some complex data can be applied Principal Component Analysis streamline its.
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matlab principal component analysis, PCA算法.
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统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines,
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用主成分分析法提取人脸图像特征的程序，算法理论依据是K-L变换,Principal Component Analysis with face image feature extraction process
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主元分析PCA的C代码，自己花了好几天编的，对做数据挖掘和模式识别的同志们有用,PCA principal component analysis of C code that he spent a few days for the better, and to do data mining and pattern recognition useful comrades
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稀疏PCA的优化解算法，较新的pca算法，供大家学习交流！-Optimal Solutions for Sparse Principal Component Analysis
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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.
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此程序用来对单波段图像或者多波段图像进行主成分分析，可以对主成分个数进行手动设置-This procedure used for single-band image or multi-band images, principal component analysis, the number of principal components can be manually set
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Kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with
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PCA人脸识别算法，识别率达到99 ，采用小波变换的方法及主成分分析法。-PCA face recognition algorithm, the recognition rate up to 99 , using wavelet transform methods and principal component analysis.
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Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
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里面包含主元分析PCA的Matlab代码，包括提取主元，求方差贡献率，绘制贡献率直方图等-Which contains the principal component analysis PCA of the Matlab code, including the extraction of the main element, seeking variance contribution rate, contribution rate of histogram mapping, etc.
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基于主成分分析(PCA)的人脸识别系统。-Based on principal component analysis (PCA) of face recognition systems.
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基于主成分分析的人脸识别，本程序给出了N次重复实验后各维数的识别率-Principal Component Analysis(PCA)for face recognition
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The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing
A common problem in statistical pattern recognition is feature selection or feature extraction. Feature selec
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Kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a n
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主成分分析pca算法matlab程序代码：pca标准化、协方差、特征根特征向量、方差贡献率-Principal component analysis pca algorithm matlab code: pca standardized covariance, eigenvalues eigenvectors, the variance contribution rate. . .
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主成分分析（Principal Component Analysis，PCA）， 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量，转换后的这组变量叫主成分。(Principal Component Analysis (PCA) is a statistical method. Convert a set of variables that may be relevant by orthogonal transform into a set of linearly
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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.)
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基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。
经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set.
After PCA dime
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