Visualizing Coarse to Fine

You're going to undertake the first part of a Coarse to Fine search. This involves analyzing the results of an initial random search that took place over a large search space, then deciding what would be the next logical step to make your hyperparameter search finer.

You have available:

combinations_list - a list of the possible hyperparameter combinations the random search was undertaken on.
results_df - a DataFrame that has each hyperparameter combination and the resulting accuracy of all 500 trials. Each hyperparameter is a column, with the header the hyperparameter name.
visualize_hyperparameter() - a function that takes in a column of the DataFrame and produces a scatter plot of this column's values compared to the accuracy scores

Confirm (by printing out) the size of the combinations_list, justifying the need to start with a random search.
Sort the results_df by accuracy values and print the top 10 rows. Can find clear insights just from this very small sample size? (Beware the small sample size!)
Confirm (by printing out) which hyperparameters were used in this search.
Call visualize_hyperparameter() with each hyperparameter in turn. Note any clear trends.

Take Hint (-30 XP)

Exercise

Visualizing Coarse to Fine

Instructions