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What's the bad sign there? If juniors are reaching for RF as a first-pass over say, (logistic) regression, that seems like a _great_ sign; no other approach has such a high average performance-effort ratio. For non-huge, naturally tabular problems, it usually takes me 10x or more the effort to beat the very first RF I train. Developer time matters!

If they start going to GBM's or neural nets first...I'd call _that_ a bad sign (and it happens).



I can understand why a neural networks first is bad, but I don't understand the problem with GBM's




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