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PCA is a foundational dimension reduction technique, and kNN can be used in conjunction with embeddings. k-means is still great when you have prior/domain know
by popinman322 4y ago
PCA is a foundational dimension reduction technique, and kNN can be used in conjunction with embeddings.
k-means is still great when you have prior/domain knowledge about the number of groups.
- nephanth 4y agoK-means is pretty poor when the clusters are not linearly separated, but it is the basis of a lot of more modern clustering techniques (kernel K-means if you have prior knoweledge, spectral clustering...)