I'm performing classification via cosine similarity to vector means. Normally, we reduce dimensionality of a problem in order to reduce confusion to the classifier. Mathematically, will dimensionality reduction reduce confusion to the classifier when using a distance-based approach? It doesn't seem like it would help, but only hurt (by withholding information.)




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