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It's a rather bizarre perspective, like a bicycle rental shop saying "it's feasible to go from Paris to Beijing on our bicycles, but it would take very long". You just need a faster vehicle. If you can't do something with a small dataset, that's a technology problem.
Every problem is solvable with k-NN. You "just" need enough data.
Yes, it's hiding an exponential.
And few features, k-NN is crazy sensitive to the curse of dimensionality
data generation using monte carlo or any other method (markdown tools for nlp for instance) is not the best way though for most of the real life problems
Not to mention the robustness which has not hit the KPIs yet! Most trained models change by adding/removing data, or skewing data.
“Give me a dataset large enough and some more to cross validate on, and I will move the Earth 2% farther than the current SOTA (by burning off excess rainforest mass)” —Archimuskes
Earth mover‘s distance?
Reminded me of Archimedes quotes but for data “Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.”
Correct
what about svm? do people use svm nowadays?
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