To improve the likelihood of a more accurate model, the data scientist can increasenum_evalsto 100. Increasing the number of evaluations allows the hyperparameter tuning process to explore a larger search space and evaluate more combinations of hyperparameters, which increases the chance of finding a more optimal set of hyperparameters for the model.
References:
Databricks documentation on hyperparameter tuning: Hyperparameter Tuning
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