how to find the covariance matix & eigen value

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ajith
ajith on 22 Feb 2013
In my project i implementing the PCA for an image i need to find the eigen vectors for an image using PCA. if it there any inbuilt function to find the covariance/correlation, eigen value, eigen vectors, how to find the coordinates of each data point of principal components

Answers (2)

Walter Roberson
Walter Roberson on 22 Feb 2013
cov(), eig()
  1 Comment
ajith
ajith on 22 Feb 2013
if i apply directly the pca function pca() .if it possible to know the covariance, eigon vectors

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Shashank Prasanna
Shashank Prasanna on 22 Feb 2013
The 'coeff' contains the eigen vectors of the covariance matrix and 'latent' has the eigen values of the covariance matrix. your 'coordinates of each data point of principal components' is the score.
I recommend you read the documentation of PCA to understand what the outputs mean:
But what is your intention? you can use cov and eig as walter mentioned to find the covariance and its eigen vectors and this is an intermediate step in performing PCA.
  4 Comments
ajith
ajith on 28 Feb 2013
x=double(imread('result.png'));
[pc, zscores, pcvars] = princomp(x);
it shows
>> Empty state-space model.
how to resolve it
Shashank Prasanna
Shashank Prasanna on 28 Feb 2013
Edited: Shashank Prasanna on 28 Feb 2013
Do you have the statistics toolbox? because princomp and pca are only available in the statistics toolbox. You can check that by typing 'ver' on the commandline.
Start fresh
>> clear all
and then execute princomp(x), copy-paste the exact error message you see from the command line if you see an error.
What is the output of :
>> which -all princomp

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