Dimensionality reduction techniques for clustering.
I think LDA is used for both supervised and unsupervised problems.
LDA is matrix based dimensionality reduction technique.
LDA can only be used in supervised settings. It maximizes the inter-class distance while minimizing the intra-class spread.
PCA is a linear method that is useful for unsupervised dimensionality reduction.
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