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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

1. In machine learning, what does "overfitting" refer to?

A) A model that has too much complexity and fits the training data too closely
B) A model that performs well on new, unseen data
C) A model that is undertrained and has high bias
D) A model that is unable to make predictions

2. What is the primary role of a data warehouse in an organization?

A) Data exploration and visualization
B) Data transformation and cleaning
C) Long-term data storage and analysis
D) Real-time data analysis

3. When building a recommendation system, what does "collaborative filtering" rely on?

A) The popularity of items
B) Item-based clustering
C) The past behavior or preferences of users
D) The characteristics of the items being recommended

4. Which of the following metrics is commonly used to evaluate the performance of a binary classification model in a machine learning pipeline?

A) Accuracy
B) Mean Absolute Error (MAE)
C) R-squared
D) Root Mean Squared Error (RMSE)

5. Refer to the exhibit below:

Based on the output from the Data Exploration node shown in the exhibit, which variable has the most thin tails (most platykurtic distribution)?

A) Logi_rfm4
B) Logi_rfm8
C) Logi_rfm6
D) Logi_rfm12

Solutions: