The main ideas behind PCA are actually super simple and that means it’s easy to interpret a PCA plot: Samples that are correlated will cluster together apart from samples that are not correlated with them. In this video, I walk through the ideas so that you will have an intuitive sense of how PCA plots are draw. If you’d like more details, check out my full length PCA video here:
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0:00 Awesome song and introduction
0:27 Motivation for using PCA
1:23 Correlations among samples
3:36 PCA converts correlations into a 2-D graph
4:26 Interpreting PCA plots
5:08 Other options for dimension reduction