“Combining principal component analysis (PCA) and kmeans clustering seems to be a pretty popular 1-2 punch in data science. While there is some debate about whether combining dimensionality reduction and clustering is something we should ever doIn some contexts you may want to do feature selection
“Combining principal component analysis (PCA) and kmeans clustering seems to be a pretty popular 1-2 punch in data science. While there is some debate about whether combining dimensionality reduction and clustering is something we should ever doIn some contexts you may want to do feature selection
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Tony’s Blog - Tired: PCA + kmeans, Wired: UMAP + GMM
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