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Wait... That's what dimensionality reduction is for. I can interpret 3 PCA dimensions pretty damn well since I can figure out the covariance explained by each d
by Der_Einzige 7y ago
Wait... That's what dimensionality reduction is for. I can interpret 3 PCA dimensions pretty damn well since I can figure out the covariance explained by each dimension of my original dimensions
- bitL 7y agoYeah, but your accuracy also drops. You might end up with interpretable underwhelming solution instead of non-interpretable SOTA.