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Help with PCA analysis

Asked by Elise
on 19 Sep 2013

I have a set of measurements of wrist movements. It contains data about the movements in x,y,z translations and x,y,z rotations - so it has 6 dimensions.

I used:

[coeff,score,~,~,explained,~] = pca(E); 

Explained gives me the following result:


From this I see that 80% of the data is in the first two principle components.

I assume that these 2 principle components form a plane. How do I use coeff to see how this plane is orientated?

Thanks in advance for helping me out!


When you say "see how this plane is orientated", do you literally mean a visualization? It's a challenge to show a (2-D) plane embedded in a 6-D space.

on 20 Sep 2013

Good question, visualizing would be preferable, but I can see that that would be difficult.

I quess what I want to know is how much of each original component can be found in the first two principal components. For this case: how much translation v.s. rotation can be found in the first to principle components.

I know this should be found in coeff/score, I just can not figure out how to interpret these.

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