amine moutaouakil

 

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principal components analysis

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06 Feb 2009		Principal Component Analysis Efficient, accurate principal component analysis Author: Mark Tygert	sparse, pca, probability, principal components ..., statistics, mathematics	62	6	4.66667 4.7 | 7 ratings

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26 Jan 2012		Active Shape Model (ASM) and Active Appearance Model (AAM) Cootes 2D/3D Active Shape & Appearance Model for automatic image object segmentation and recognition Author: Dirk-Jan Kroon	active appearance mod..., active appearance, active shape, faces, aam, 2d	339	49	4.73333 4.7 | 16 ratings
05 Jan 2012		Nonlinear fuzzy robust pca Implementation of a nonlinear fuzzy robust pca. Author: Pasi Luukka	pca, fuzzy, chemometrics	46	0
18 Nov 2011		Orthogonal Linear Regression in 3D-space by using Principal Components Analysis Orthogonal Linear Regression by using PCA Author: Ivo Petras	pca, orthogonal regression, total least squares, probability, statistics, fitting	60	0
16 Nov 2011		Linear Discriminant Analysis Code this function converts data from its original space to LDA space. Author: Muhammet	lda, linear discriminant, multi class	36	1
17 Oct 2011		Feature Analysis This program analyzes an arff file (weka) Author: Iftekhar Tanveer	arff, lda, feature selection, visualization, weka, pca	46	2

Comments and Ratings Matching amine's Watch List			1-5 of 10
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11 May 2011	Principal Component Analysis Efficient, accurate principal component analysis	jose vanaclocha	Hello. My name is Jose. I'm student of UPV in spain. I need help for implement the PCA and PLS algotithms trhogth SVD method. If someone can help me.... The only one that i have is this: % PCA MEDIANTE SVD % ENTRADAS % A Matriz de datos % SALIDAS % u % S % V % MATRIZ DE DATOS A = [1 2;3 4] % CALCULAMOS EL TAMAÑO DE LA MATRIZ [M,N] = size(A); % CALCULO DE LA MEDIA mn = mean(A,2); B = A - repmat(mn,1,N); % CONSTRUCCION DE LA MATRIZ Y stdA=std(A) Y = stdA/ sqrt(N-1); % APLICAMOS SVD [u,S,PC] = svd(Y); % CALCULAMOS LOS OUTPUTS S = diag(S); V = S .* S;	4
30 Oct 2009	Principal Component Analysis Efficient, accurate principal component analysis	nsmaan Singh	Hello, This is the first time I am trying to use matlab. Since I only have fairly small job to do I am not trying to delve too deep. I have a 5000x5000 matrix like this (just a part...n=till 5000) 1.0 0.2 0.3 0.1.........n 0.2 1.0 0.1 0.3.........n 0.3 0.1 1.0 0.2..........n ... ... ... ... n n n n I have been using SpotFire so far for PCA analysis, but this matrix is too huge for its memory, hence trying matlab. Any help on how i can decompose it into 3 PC's would be greatly appreciated. Thank you	Comment only
06 May 2009	Principal Component Analysis Efficient, accurate principal component analysis	Wolfgang	But the same question as Jon Jackson. Is it possible to get the explained variances when i just compute (for example) the first three components?	Comment only
06 May 2009	Principal Component Analysis Efficient, accurate principal component analysis	Wolfgang		5
04 Apr 2009	Principal Component Analysis Efficient, accurate principal component analysis	Jon Jackson	Works really well, thanks. Is it possible to get the percentage of the explained variance for each component?	4