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Questions tagged [svd]

Singular Value Decomposition (SVD) is a factorization of a real or complex matrix, with many useful applications in signal processing and statistics.

The Singular Value Decomposition (SVD) of a rectangular matrix A is a decomposition of the form:

A = U S V*

where U and V are orthogonal matrices, and S is a diagonal matrix containing the singular values.

In scientific software for statistical computing, function svd computes this decomposition.

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How to show the row names and column names for the Golf SVD example?

I tried using R in IdeOne to display the SVD results from the Single Value Decomposition (SVD) tutorial using the R code from Dr. Jerry A Smith. The IdeOne link is here, and here's what I…
pageman
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How to determine test error for Simon Funk's incremental SVD method

I'm trying to implement this for a ratings dataset that's similar to Netflix, and I've gotten it to "work"; the training error is driven toward 0 after each iteration / more features are added. How do I determine how well this will predict a test…
Jon
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using singular value decomposition (svd) in quadratic regression

In order to do a quadratic regression on a rather large data set I would like to solve the following equation using svd(singular value decomposition): B(nx1)=A(nx3)*X(3x1) I am thinking to use matlab for that, any tips? the goal is to compute matrix…
C graphics
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residuals of plane fitting using svd

I am fitting a best-fit plane for a set of points(X,Y,Z coordinates) using Singular Value Decomposition. So I use M = [x y z 1] [u s v] = svd(M) p = v(:,4) Now I want the residuals of the points. I know I can compute the planar equation to get the…
shunyo
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Using Principal Components Analysis (PCA) on binary data

I am using PCA on binary attributes to reduce the dimensions (attributes) of my problem. The initial dimensions were 592 and after PCA the dimensions are 497. I used PCA before, on numeric attributes in an other problem and it managed to reduce the…
user1769484
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Transposing a matrix before doing a SVD with Jama

So I'm using Jama (Java matrix library) to compute the SVD of a matrix A. The problem is that Jama only works if A (mxn) is a matrix where m >=n and I'm using one where m I've read this can be solved by doing A' (transpose). So that if you have…
Jared Joke
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Is it possible to reverse svds

Is it possible to reverse the following in matlab: [U,S,V]=svds(fulldata,columns);
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MATLAB SVD singular value ordering

MATLAB documentation of SVD states that the diagonal matrix returned has singular values in decreasing order. Is there a way to find out what the natural ordering of singular values would be? The reason I ask is because the singular values…
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Large Sparse Matrix Eigendecomposition in JAVA

I am looking for a linear algebra library in Java which can handle large "sparse" matrices of size (say 1 million by 1 million) and perform decompositions like SVD,LU on the matrices. I looked around and tried COLT, however it can only handle…
Blade Runner
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Issues in Java Matrices Libraries

I'm working in a project that need to get SVD (Single Values Decomposition) for a matrix of 74000 X 640 dimension. I tried those three libraries: Jama, efficient Java Matrix library (EJML), and OjAlgo.I choose these three based on the Java Matrix…
sakurami
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Multiplying SVD components of a matrix in OpenCV

I applied SVD to a CV_32FC1 cvMat and modified some values in the 'u' component. Now I am trying to multiply the 'u, 'w' and 'vt' components to get a single matrix A. But OpenCV fails to multiply the matrices with the following error. OpenCV Error:…
blacktooth
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Creating a term document matrix in java for LSI implementation

I am doing a search engine project using vector space model for which i need to create a Term-Document Matrix and then apply SVD on it. Should i have the term as the row and document as columns ? I am doing it in java so it should be like : …
Deepankar Bajpeyi
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How to determine scaling factor so that covariance matrix has a first element of 1?

I have data which I need to center and scale so that is centered around the origin. Then the data needs to be rotated so that the direction of maximum variance is on the x-axis. The mean of the data and the covariance is then calculated. I need the…
luke417
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Jama getS gives exception

I am applying SVD to a term - document matrix that i have already created.The matrix is a double array of the form : public static double[][] tdidf; tdidf = new double[listOfFiles.length][keywordList.size()]; But when i apple svd : …
Deepankar Bajpeyi
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pca in R with princomp() and using svd()

Possible Duplicate: Comparing svd and princomp in R How to perform PCA using 2 methods (princomp() and svd of correlation matrix ) in R I have a data set…
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