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Coarse to Fine Iterations

You will now visualize the first random search undertaken, construct a tighter grid and check the results. You will have available:

  • results_df - a DataFrame that has the hyperparameter combination and the resulting accuracy of all 500 trials. Only the hyperparameters that had the strongest visualizations from the previous exercise are included (max_depth and learn_rate)
  • visualize_first() - This function takes no arguments but will visualize each of your hyperparameters against accuracy for your first random search.

If you wish to view the visualize_first() (or the visualize_second()) function definition, you can run this code:

import inspect
print(inspect.getsource(visualize_first))

Cet exercice fait partie du cours

Hyperparameter Tuning in Python

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Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Use the provided function to visualize the first results
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