this post was submitted on 22 Feb 2025
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Machine Learning

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[D] Dimensionality reduction is bad practice? (old.reddit.com)
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The original was posted on /r/machinelearning by /u/Ready_Plastic1737 on 2025-02-21 17:30:22+00:00.

I was given a problem statement and data to go along with it. My initial intuition was "what features are most important in this dataset and what initial relationships can i reveal?"

I proposed t-sne, PCA, or UMAP to observe preliminary relationships to explore but was immediately shut down because "reducing dimensions means losing information."

which i know is true but..._____________

can some of you add to the ___________? what would you have said?

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