learning_rate and n_estimators Are One Parameter, Not Two — Here's the Number That Proves It

The One-Line Summary: Grid-searching learning_rate against n_estimators wastes most of your compute, because the boosting model that comes out depends almost entirely on their product — measured across seven learning rates, the optimal lr × n_estimators held at 4.4 on classification and converged to about 3.0 on regression, so the right move is to fix the rate as low as your patience allows and let early stopping pick the count. The Grid You Should Stop Searching This is the search space almost…