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Hyperparameter Tuning

Topic: Optimization

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Grid Search

Grid search tries all combinations of parameter values.

GridSearchCV

GridSearchCV(model, param_grid, cv=5). param_grid is dict of parameters to try.

cv determines cross-validation folds. Scoring metric defaults to accuracy.

Best parameters: grid_search.best_params_. Best score: grid_search.best_score_.

Random Search

RandomizedSearchCV samples parameter combinations. More efficient for large spaces.

n_iter controls number of combinations. random_state ensures reproducibility.

Key Takeaways

  1. Grid search exhaustively tries all combinations
  2. Random search is more efficient for large spaces
  3. Cross-validation guides parameter selection

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