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

1. Which type of model is typically used for time-series forecasting?

A) Decision Trees
B) K-Means Clustering
C) Logistic Regression
D) AutoRegressive Integrated Moving Average (ARIMA)

2. What is "model retraining" in the context of model deployment?

A) The process of feature selection
B) The process of building the initial model
C) Periodically updating and improving a deployed model with new data
D) The process of data preprocessing

3. What is the primary objective of model validation during the model assessment phase?

A) To create synthetic data
B) To assess the accuracy of the model
C) To ensure the model generalizes well to new, unseen data
D) To build a model from scratch

4. 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_rfm8
B) Logi_rfm4
C) Logi_rfm6
D) Logi_rfm12

5. Which technique is commonly used for feature scaling or normalization in machine learning pipelines?

A) Standardization
B) Principal Component Analysis (PCA)
C) One-Hot Encoding
D) Decision Trees

Solutions: