Reduce data dimension using PCA
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pca() outputs the coefficient of the variables and principal components of a data. Is there any way to reduce the dimension of the data (340 observations), let say from 1200 dimension to 30 dimension using pca()?
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Vassilis Papanastasiou
2021-12-17
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Hi Hg,
What you can do is to use pca directly. Say that X is of size 340x1200 (340 measurements and 1200 variables/dimensions). You want to get an output with reduced dimensionaty of 30. The code below will do that for you:
p = 30;
[~, pca_scores, ~, ~, var_explained] = pca(X, 'NumComponents', p);
- pca_scores is your reduced dimension data.
- var_explained contains the respective variances of each component.
I hope that helps.
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2021-12-17
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