# How do i obtain only the first principal component?

13 visualizzazioni (ultimi 30 giorni)
sidra il 1 Ott 2013
Risposto: Andrew Knyazev il 12 Ago 2018
For certain measurements i need to obtain only the numeric value of the first principal component from the matrix. Can someone please tell me how do i go about it?
##### 1 CommentoMostra NessunoNascondi Nessuno
sidra il 23 Ott 2013
Any suggestions?

Accedi per commentare.

### Risposta accettata

Jan il 23 Ott 2013
Modificato: Jan il 23 Ott 2013
I'm not sure, if I fully understand your question. I doubt however, that there is a straightforward method for calculating the eigenvector corresponding to the largest eigenvalue of the covariance matrix without calculating all eigenvalues first (at least not for non-sparse matrices).
If you want the first principal component of the (m x n)-matrix A containing m measurements as row vectors you would in general do the following:
A = randn(100, 20); % artificial sample matrix
c_A = cov(A);
[V, ~], eigs( c_A );
p_1 = V( :, 1 );
which gives you the direction of the first principal component in the variable p_1.
##### 1 CommentoMostra NessunoNascondi Nessuno
sidra il 29 Ott 2013
Thank you so much jan :)

Accedi per commentare.

### Più risposte (1)

Andrew Knyazev il 12 Ago 2018
https://www.mathworks.com/matlabcentral/fileexchange/48-lobpcg-m can be used as the method for calculating the eigenvector corresponding to the largest eigenvalue of the covariance matrix without calculating all eigenvalues, or even without explicitly calculating the covariance matrix itself.
##### 0 CommentiMostra -1 commenti meno recentiNascondi -1 commenti meno recenti

Accedi per commentare.

### Categorie

Scopri di più su Dimensionality Reduction and Feature Extraction in Help Center e File Exchange

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!