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Search - principal component analysis matl - List
[
matlab
]
PCA_Matlab_ana
DL : 0
主成分分析是把多个指标化为少数几个终合指标的一种统计分析方法。本源代码为matlab中源代码,并添加了相应的分析注解-Principal Component Analysis is more than a few indicators as a final indicator of a statistical analysis method. Source code for which the source code Matlab, and add the corresponding analysis notes
Update
: 2025-02-19
Size
: 4kb
Publisher
:
东
[
AI-NN-PR
]
IntroMatlab_codepls
DL : 0
PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.
Update
: 2025-02-19
Size
: 264kb
Publisher
:
郭大
[
matlab
]
subspace
DL : 0
子空间分解matlab程序。采用PCA主成元分析方法。-Subspace Decomposition matlab procedures. Using PCA Principal Component Analysis.
Update
: 2025-02-19
Size
: 1kb
Publisher
:
shiyu
[
Algorithm
]
ppca
DL : 0
Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal % component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The variable VAR contains the off-subspace variance (which is assumed to be spherical), while the vector LAMBDA contains the variances of each of the principal components. This is computed using the eigenvalue and eigenvector decomposition of X.-Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA (X, PPCA_DIM) computes the principal component subspace U of dimension PPCA_DIM using a centred covariancematrix X. The variable VAR contains the off-subspace variance (whichis assumed to be spherical ), while the vector LAMBDA contains thevariances of each of the principal components. This is computedusing the eigenvalue and eigenvector decomposition of X.
Update
: 2025-02-19
Size
: 1kb
Publisher
:
西晃云
[
AI-NN-PR
]
kpca
DL : 1
kpca算法的matlab源程序,基于核的主成分分析的源程序-KPCA algorithm matlab source, kernel-based principal component analysis of the source
Update
: 2025-02-19
Size
: 2kb
Publisher
:
曲伟
[
Algorithm
]
itoolbox
DL : 0
包含间隔偏最小二乘,组合偏最小二乘,和间隔主成分分析-Contains the interval partial least squares, combination of partial least squares, and spacing of principal component analysis
Update
: 2025-02-19
Size
: 911kb
Publisher
:
zwerbc
[
matlab
]
kernel_pca
DL : 0
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 a non-linear mapping.
Update
: 2025-02-19
Size
: 2kb
Publisher
:
Karthikeyan
[
matlab
]
Principal-component-analysis-matlab
DL : 0
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.m: The purpose of this program is to achieve edge detection drawprim.m: to find the location of the maximum principal component, which in the original image in the draw practical.m: a principal components process, edge detection and principal component extraction prin.m: princomp function of the program is to extract the principal component matrix
Update
: 2025-02-19
Size
: 17kb
Publisher
:
李仕诚
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