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It can be argued that some algorithms like Random Forests don't impose a generalization penalty as you increase the number of parameters (forests).
by elyase 10y ago
It can be argued that some algorithms like Random Forests don't impose a generalization penalty as you increase the number of parameters (forests).
- apathy 10y agoRF is appallingly difficult to re-use for inference, though. At least with a DNN or CNN you can pop open the hood and see what the model is doing at various points. Tradeoffs, tradeoffs everywhere. It's almost like traditional mathematical statistics has something to offer them fancy machine learners. (Breiman was a professor of statistics, after all... ahead of his time, but no less a statistician.)