Accessible explanation of the logic principal component analysis and an example of how companies can use PCA in finance.
In a recent post, we covered one of the most widely used data clustering algorithms K-means.
Here, we’ll shed some light on a bedrock technique for dimensionality reduction (applied extensively in probability and statistics) – principal component analysis (PCA).
What’s curious about PCA is that it’s not a dimensionality reduction method per se, despite mostly being advertised as such. Actually, it transforms data in a certain way to make it amenable to reduction later.
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