Set reg_lambda=0 for scikit-learn-like random forest classes. #4558
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These are the experiments that led to this, soon to be published in a blog. L2 penalty only increases bias in random forest models, whereas boosting models can compensate for this bias by boosting more rounds. I think we should set lambda to 1e-5 instead of 0 to prevent numerical instability in weight calculation -G/(H+ lambda) as the hessian tends to 0. |
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Done. |
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