Is it possible to index which variables to extract after Principle Component Analysis?

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sh10101 2017-1-13

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评论： sh10101 2017-1-14

Hi All,

I am a little confused as to how I can determine which variables I want after running my data matrix X through the pca funtion.

[coeff,score,latent,tsquared,explained,mu] = pca(X);

I have a 1000x16 dataset. I know from the 'explained' output that 95% of my feature variability can be explained by 7 variables.

Is there a way of determining which 7 variables (which columns numbers from the original X matrix) these are through indexing from the original X matrix,coeff, scores matrix?

Any help would be greatly appreciated here.

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Answer 1

the cyclist 2017-1-13

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编辑：the cyclist 2017-1-14

It will not be 7 of your original variable that explain 95% of the variation. This is an important concept to understand.

Rather, it will be 7 of the new variables, each of which is a linear combination of your original variables, that will explain the variation. Each column of coeff is the weight of the original variable. The first 7 columns of coeff are what you want.