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Machine Learning 47: Random Projections
We introduce random projections as an alternative approach to dimensionality reduction. We motivate it as preserving all pairwise distances among input feature vectors. We then introduce the Johnson-Lindenstrauss transform and prove that it preserves the distances between all input feature vectors with high probability when embedding into ...
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