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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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利用主成分分析方法，对TE模型产生的故障数据故障1进行故障检测-Using principal component analysis, on the TE model failure data generated by a fault detection fault
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高维PCA
参考文献：
MPCA Multilinear Principal Component Analysis of Tensor Objects-High-dimensional PCA References: MPCA Multilinear Principal Component Analysis of Tensor Objects
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PCA主成分分析，用于人脸识别，特征提取等-PCA principal component analysis for face recognition, feature extraction, etc.
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一个用于聚类的工具箱，内有主元分析、模糊等技术的Matlab源代码和应用实例程序Demo。-One for clustering toolbox, with principal component analysis, fuzzy techniques, such as Matlab source code and application procedures for Demo.
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PCA代码
主成分分析代码
适合初学人脸识别的朋友学习使用-PCA principal component analysis source code suitable for beginner learning to use face recognition friend
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这是一个主成分分析的matlab程序，非常有用。-This is a principal component analysis of matlab procedures, very useful.
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为解决PCA不适合多指标综合分析中非线性主成分分析的问题 ,采用核主成分分析 (kpca)方法 ,对我国不同地区 16种腐乳的品质进行了综合评价。
-PCA is not suitable to address the many indicators of a comprehensive analysis of non-linear principal component analysis of the problem, using Kernel Principal Component An
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基于多元线性回归、偏最小二乘、神经网络、卡尔漫滤波、径向基网络、主成分分析等等的程序。可用于建模和预测。-Based on multiple linear regression, partial least squares, neural networks, Carl diffuse filtering, radial basis networks, and so on principal component analysis procedure. Can be used for modelin
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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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PCA 主成分分析在人脸识别中的应用 基于主成分分析理论对不同人脸库进行学习 总结“经验”并将“经验”用于对人脸的识别中-PCA Principal Component Analysis for Face Recognition Based on principal component analysis theory of different learning face database summary of " experience" and " experience
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主成分分析，人脸识别，模式识别，对图像处理有点帮助-Principal component analysis, face recognition, pattern recognition, image processing for a little help
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基于核函数的主分量分析法源代码，可用于人脸识别-Kernel-based principal component analysis source code, can be used for face recognition
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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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核主成分分析中使用多项式核函数时的MATLAB代码，有注释，易看懂。-Kernel Principal Component Analysis in the use of polynomial kernel function of the MATLAB code, annotated, easy read.
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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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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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MPCA Multilinear Principal Component Analysis of Tensor Objects with MATLAB
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主成分分析.mht：介绍主成分分析的文章
edgepick.m：本程序的目的是实现边缘检测
drawprim.m：找到最大主分量所在的位置，从而在原图象中绘出
practical.m：一个主分量的程序，边缘检测和主分量提取
prin.m：该程序是用princomp函数来提取矩阵的主成分-Principal component analysis. Mht: the article describes the principal component analysis edgepick
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