Manage Data Transformation to Conduct Data Preparation PMI-CPMAI Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which of the following is a feature selection method?

   • AMin-max scaling
   • BSynthetic data generation
   • CData augmentation
   • DFilter method
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A data science team is preparing features for a linear regression model that predicts house prices. The dataset includes features like 'number_of_bedrooms' (1-6) and 'square_footage' (500-5000). The team wants to ensure that all features have zero mean and unit variance to improve the convergence of the gradient descent optimization. Which preprocessing technique should they apply?

   • ARobust scaling
   • BMin-max scaling
   • CLog transformation
   • DZ-score standardization
   Reveal Solution Discussion Select an answer first
4. 8application · medium

   A data science team is building a churn prediction model. The dataset contains a 'customer_age' feature ranging from 18 to 70 and an 'annual_income' feature ranging from $20,000 to $250,000. The team plans to use a k-nearest neighbors classifier, which is sensitive to feature scales. They want to preserve the original distribution shape of each feature while bringing them to a comparable range. Which approach should the team use?

   • AApply log transformation to income and min-max scaling to age
   • BApply z-score standardization to both features
   • CApply min-max scaling to both features
   • DApply robust scaling to both features
   Reveal Solution Discussion Select an answer first
5. 9expert · hard

   A financial institution is developing a model to detect fraudulent transactions. The dataset is highly imbalanced, with only 0.1% fraudulent transactions. They have privacy concerns about sharing real customer data with external partners for model development. They decide to generate synthetic data that mimics the real data distribution. Which approach should they use to ensure the synthetic data is realistic and preserves privacy?

   • AUse SMOTE to oversample the minority class
   • BUse a generative adversarial network (GAN) trained on the real data
   • CDuplicate the existing minority class samples
   • DRandomly generate data using a uniform distribution
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   Which element should be included in documentation of a transformation process?

   • AThe deployment environment details
   • BThe rationale for each transformation step
   • CThe final model accuracy
   • DThe model's hyperparameters
   Reveal Solution Discussion Select an answer first