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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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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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主成分分析和偏最小二乘SquaresPrincipal成分分析（ PCA ）和偏最小二乘（ PLS ） ，广泛应用于工具。此代码是为了显示他们的关系，通过非线性迭代偏最小二乘（ NIPALS ）算法。
,Principal Component Analysis and Partial Least SquaresPrincipal Component Analysis (PCA) and Partial Least Squares (PLS) are widely used tools. Thi
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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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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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使用Fuzzy Cluster Mean (FCM)與Principal component analysis (PCA)分類Yeast Data-Yeast data will be classified by means of Fuzzy Cluster Mean (FCM)and Principal component analysis (PCA) based on matlab.
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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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26页PPT，详细介绍主成分分析（Principal Component Analysis，PCA）的概念-26 PPT, details of principal component analysis (Principal Component Analysis, PCA) concept of
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神经计算的实验作业。用principle components analysis计算模式的主分量。提取线性输入的特征。-Neural computing experiment operations. Computing model using principle components analysis of the principal component
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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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用Matlab实现主成分分析（PCA)算法.-Principal component analysis using Matlab implementation (PCA) algorithm.
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一个关于主成分分析的matlab演示，十分有用-A principal component analysis on matlab demo, very useful
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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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用于主成分分析（PCA）,包括，原变量相关系数矩阵的特征向量和特征值的求解，主成分的提取，载荷值的确定等-Used principal component analysis (PCA), including the original variable correlation matrix eigenvectors and eigenvalues of the solution, the main component of the extract, load value
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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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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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