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

1. In reinforcement learning, what is the agent's objective?

A) To generate synthetic data
B) To learn from labeled data
C) To maximize a cumulative reward over time
D) To make predictions

2. What is the primary goal of hyperparameter tuning during model building?

A) To optimize the settings that control the model's learning process
B) To add more features to the model
C) To increase model complexity
D) To improve data preprocessing techniques

3. 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_rfm12
C) Logi_rfm6
D) Logi_rfm8

4. What is overfitting in machine learning, and how can it be addressed in a pipeline?

A) Overfitting is not a concern in machine learning pipelines.
B) Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.
C) Overfitting occurs when the model is too complex and overperforms.
D) Overfitting occurs when the model is too simple and underperforms.

5. Which statements are true for the F1 score?
(Choose 2.)

A) F1 score is applicable to a model with a binary target.
B) F1 score is applicable to a model with an interval target.
C) F1 score is calculated based on a cut off value.
D) F1 score is calculated based on a depth value.

Solutions: