Week 6 — Lesson 4: Hyperparameter tuning with GridSearchCV

3 min

max_depth, n_estimators and min_samples_leaf are settings you choose before training; the NorthPeak forest cannot learn them from the rows. In Exercise 1 you tuned one of them by hand, with a loop over depth. With three settings the loop becomes a triple loop and the runs get mixed up. GridSearchCV builds every combination of a small grid, scores each one with cross-validation and refits the best. This lesson runs a 12-combination grid on the 10,720 training rows and reads the result table.

Preview — the rest of the lesson is for enrolled readers.

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This lesson is part of the “Week 6 — Model selection and validation” module

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