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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. 1foundation · easy

    Which strategy is most effective for reducing the wall-clock time of hyperparameter tuning when computational resources are limited?

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  2. 2application · medium

    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?

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  3. 3foundation · easy

    In k-fold cross-validation, what does the 'k' represent?

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  4. 4application · medium

    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. 5foundation · easy

    For k-means clustering, what is the role of the hyperparameter k?

    Select an answer first
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