Objective 3.3 Carry Out Feature Engineering CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A data scientist wants to rank the importance of features in a dataset using a tree-based model. Which technique can they use?

   • AOne-hot encoding
   • BRandom forest feature importance
   • CPCA
   • DLow-variance filter
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   What is the main reason for using dummy encoding (k-1 columns) instead of one-hot encoding (k columns) in linear models?

   • ATo reduce the number of features and improve interpretability
   • BTo avoid perfect multicollinearity among the dummy variables
   • CTo preserve the ordinal relationship between categories
   • DTo handle missing values more effectively
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   What does the trim operation do in text manipulation?

   • AIt converts all characters to uppercase.
   • BIt splits a string into multiple parts based on a delimiter.
   • CIt removes leading and trailing whitespace or specified characters.
   • DIt reverses the order of characters in a string.
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   What is the key advantage of label/ordinal encoding over one-hot encoding?

   • AIt avoids any assumption of order among categories.
   • BIt preserves the ordinal relationship between categories.
   • CIt creates more columns, which can improve model performance.
   • DIt uses the target variable to encode categories.
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   Which of the following is an example of converting a date column into a useful feature?

   • AExtracting the day of the week as a numeric value (0-6)
   • BReversing the date string
   • CTrimming whitespace from the date string
   • DCreating a binary column for each date
   Reveal Solution Discussion Select an answer first