Engineer Features for Models SNOWPRO-ADVANCED-DATA-SCIENTIST Practice Questions (Page 9)

Questions 41–45

1. 41foundation · easy

   Which of the following is an example of creating a new feature from existing data?

   • ASelecting a subset of existing columns to use in the model
   • BRemoving duplicate rows from the dataset
   • CSplitting the dataset into training and test sets
   • DCalculating the ratio of two existing numeric columns
   Reveal Solution Discussion Select an answer first
2. 42foundation · easy

   What type of feature is a rolling average over a fixed window of past observations?

   • ASeasonal component
   • BRolling statistic
   • CLagged value
   • DTrend indicator
   Reveal Solution Discussion Select an answer first
4. 43foundation · easy

   What is a key benefit of designing a reproducible feature engineering pipeline?

   • AIt ensures consistent feature transformations across training and inference
   • BIt automatically selects the best model algorithm
   • CIt eliminates the need for model evaluation
   • DIt guarantees the model will have high accuracy
   Reveal Solution Discussion Select an answer first
5. 44foundation · easy

   Which practice is essential for a reproducible feature engineering pipeline?

   • AManually applying transformations to new data
   • BDropping all features with missing values
   • CUsing a different random seed for each run
   • DVersioning the code and data transformations
   Reveal Solution Discussion Select an answer first
6. 45foundation · easy

   Which feature selection approach uses a model's performance to iteratively add or remove features?

   • AWrapper method
   • Bt-SNE
   • CFilter method
   • DEmbedded method
   Reveal Solution Discussion Select an answer first