PRINCIPAL COMPONENT ANALYSIS,using C++ language
標(biāo)簽： PRINCIPAL COMPONENT ANALYSIS language
上傳時間： 2013-12-17
上傳用戶：shizhanincc
Performs PRINCIPAL Component Analysis cross validation to determine the true rank of an X-block.
標(biāo)簽： validation Component PRINCIPAL determine
上傳時間： 2013-12-05
上傳用戶：aig85
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.
標(biāo)簽： Component PRINCIPAL Analysis bilinear
上傳時間： 2016-02-07
上傳用戶：zuozuo1215
A Tutorial on PRINCIPAL Component Analysis.PRINCIPAL component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box.
標(biāo)簽： PRINCIPAL Component component Tutorial
上傳時間： 2016-04-14
上傳用戶：aysyzxzm
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.
標(biāo)簽： Probabilistic Components PRINCIPAL Analysis
上傳時間： 2016-04-28
上傳用戶：qb1993225
pca人臉識別This package implements basic PRINCIPAL Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標(biāo)簽： implements PRINCIPAL Component Analysis
上傳時間： 2014-01-03
上傳用戶：佳期如夢
PCA人臉識別 This package implements basic PRINCIPAL Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標(biāo)簽： implements Component PRINCIPAL Analysis
上傳時間： 2016-06-25
上傳用戶：trepb001
PCA人臉識別 This package implements basic PRINCIPAL Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標(biāo)簽： implements Component PRINCIPAL Analysis
上傳時間： 2016-06-25
上傳用戶：hakim
PCA人臉識別 This package implements basic PRINCIPAL Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標(biāo)簽： implements Component PRINCIPAL Analysis
上傳時間： 2016-06-25
上傳用戶：cylnpy
PCA人臉識別 This package implements basic PRINCIPAL Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標(biāo)簽： implements Component PRINCIPAL Analysis
上傳時間： 2013-12-16
上傳用戶：JIUSHICHEN
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