Supervised Learning DY0-001 Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A data scientist uses KNN to predict a customer's annual spending (a continuous value) based on age and income. What is the prediction for a new customer?

   • AThe mode of spending among the k nearest neighbors
   • BA linear combination of age and income
   • CThe average spending of the k nearest neighbors
   • DThe spending of the single most similar customer
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   What is the primary goal of association rule mining?

   • ATo cluster similar data points
   • BTo classify data into predefined classes
   • CTo discover interesting relationships between items in a dataset
   • DTo predict a continuous target variable
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   What type of outcome is logistic regression designed to predict?

   • AA continuous numeric value
   • BA binary categorical outcome
   • CA multi-class outcome with no ordering
   • DA time series forecast
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   Which algorithm is commonly used to generate association rules from large datasets?

   • AGradient descent
   • BK-means
   • CDecision tree
   • DApriori algorithm
   Reveal Solution Discussion Select an answer first
6. 10expert · hard

   A healthcare analytics team is building a model to predict whether a patient has a rare disease (1% prevalence). They have 500 features including many lab tests that are highly correlated with each other. The team needs a model that is computationally efficient and can handle the high-dimensional correlated features. They are comparing Naive Bayes and logistic regression. Which is the better choice and why?

   • ANaive Bayes, because it is more accurate with rare diseases
   • BLogistic regression, because it assumes feature independence which is true for lab tests
   • CNaive Bayes, because it handles correlated features well due to its independence assumption
   • DLogistic regression with L2 regularization, because it can handle correlated features and provides better-calibrated probabilities for the rare disease
   Reveal Solution Discussion Select an answer first