I used PCA on 9-D data. I want to plot PCs direction

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farshad jahangiri 2022-9-28

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1814045-i-used-pca-on-9-d-data-i-want-to-plot-pcs-direction

回答： the cyclist 2022-9-29

采纳的回答： the cyclist

data.txt

在 MATLAB Online 中打开

Hi , I extract 2 PC and know I want to plot direction of PCs but I don't know how.

I attached data and code

clc;

clear;

data=importdata('data.txt');

n_data=zscore(data);

[coeff,scores,latent] = pca(n_data,'Algorithm','eig');

p=scatter(scores(:,1),scores(:,2),'filled')

p =

Scatter with properties: Marker: 'o' MarkerEdgeColor: 'none' MarkerFaceColor: 'flat' LineWidth: 0.5000 XData: [-2.6987 -2.9086 -2.6022 -2.7088 -2.5972 -2.6443 -2.4184 -2.6105 -2.6442 -2.6342 -2.7498 -2.8929 -3.0329 -2.9947 -2.7199 -2.6996 -2.6480 -2.6630 -2.5890 -2.4588 -2.3512 -2.6149 -2.6046 -2.6306 -2.7813 -2.9008 -2.8532 -2.5646 … ] YData: [-1.1820 -0.3770 -1.9835 -1.6290 -1.4321 -0.6428 -1.4788 -1.7337 -1.9207 -2.0610 -2.2508 -1.8076 0.1766 -0.5802 -1.0807 -1.6126 -1.1661 -1.0277 -2.4950 -1.5415 -1.4948 -1.3786 -0.6466 0.3495 0.0197 -0.0436 0.5450 0.6005 0.2341 … ] SizeData: 36 CData: [0 0.4470 0.7410] Show all properties

xlabel('Principal Component 1');

ylabel('Principal Component 2');

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the cyclist 2022-9-28

I am confused by what you mean by "direction of PCs".

Because you are plotting the scores variable, you are plotting in principal component space (not the original coordinate space). I would say that the x- and y- axes are the "direction of the PCs" in this plot. (The other 7 PCs are orthogonal to these.)

If this does not make sense, or does not capture what you mean, maybe you could explain some more. What are you trying to illustrate?

farshad jahangiri 2022-9-29

移动：the cyclist 2022-9-29

@the cyclist Hi . I am confused about this. in some researches like this picture they showed direction of principal components. I want to show when covariance matrix changes, the PCs direction will be change.

I think we just can show this direction in not transformed data and in original axis, not transformed data (scores).

In this case How can I show the direction of PCs in original data and what data should be used instead of scores? I am confused because the scores have all 9 dimensions and can be shown in one dimension, but the original data cannot

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Answer 1

the cyclist 2022-9-29

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1814045-i-used-pca-on-9-d-data-i-want-to-plot-pcs-direction#answer_1063110

Your comment was helpful. I think the biplot function may do what you need.

The biplot illustrates what the original axes look like in (two or three dimensions of) PC space.

I think that making a biplot of the inverse of coeff would illustrate what the PC vectors look like in the original space. (I am not certain of this last statement. I'd need to think about it more, and experiment a bit.)