
SnowflakeSnowPro Advanced — Data Scientist
Domain 4Objective 3
Tune Model Hyperparameters SNOWPRO-ADVANCED-DATA-SCIENTIST Practice Questions (Page 1)
Part of the Model Development domain, which makes up ~19% of our current practice bank.
32questions here
7free pages
10concepts
Questions 1–5
- 1
Which strategy is most effective for reducing the wall-clock time of hyperparameter tuning when computational resources are limited?
Select an answer first - 2
A data scientist is using GridSearchCV to tune a random forest. They have 4 hyperparameters, each with 5 possible values. How many model fits will be performed if they use 5-fold cross-validation?
Select an answer first - 3
In k-fold cross-validation, what does the 'k' represent?
Select an answer first - 4
A data scientist is tuning a random forest classifier for a binary classification problem with a highly imbalanced dataset (5% positive class). They plan to use grid search with 5-fold cross-validation. Which evaluation metric should be used as the scoring function during grid search to best guide hyperparameter selection?
Select an answer first - 5
For k-means clustering, what is the role of the hyperparameter k?
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