How to apply The Kaiser rule in PCA?

4 Ansichten (letzte 30 Tage)
MUHAMMAD ALKHUDAYDI
MUHAMMAD ALKHUDAYDI am 11 Dez. 2019
Bearbeitet: Shubh Sahu am 30 Jan. 2020
Hi,
In MATLAB there is a bulid function to apply principle component analysis PCA. However, I have a problem on applying The Kaiser rule which drop all components with eigenvalues under 1. For Example I want to apply this method on the data:
X = [1 2 3 4 5 ; -1 -3 -1 2 4 ; -2 1.5 3 2 -9 ; 1 -1 0.25 2.3 2.2];
[coeff,newdata,latend,tsd,variance] = pca(X)
Please can some one help me on this. Many thanks.

Akzeptierte Antwort

Shubh Sahu
Shubh Sahu am 30 Jan. 2020
Bearbeitet: Shubh Sahu am 30 Jan. 2020
Hey!
Instead of calculating PCA go with SVD. Take under the under root of sigmas 's' and now you have eigenvalues. Check for kaiser rule and select the column with eigenvalue less than 1
X = [1 2 3 4 5 ; -1 -3 -1 2 4 ; -2 1.5 3 2 -9 ; 1 -1 0.25 2.3 2.2];
[u,s,v] = svd(X)
Please refer to this link for further information

Weitere Antworten (0)

Kategorien

Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und File Exchange

Tags

Community Treasure Hunt

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

Start Hunting!

Translated by