SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406

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SASInstitute A00-406 Exam Syllabus Topics:

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

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

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

2. What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

A) To prevent overfitting and reduce model complexity
B) To add more features to the model
C) To speed up model training
D) To increase model complexity

3. In reinforcement learning, what is the "reward signal"?

A) The final prediction made by the model
B) A numerical value that indicates the performance of an action taken by the agent
C) The accuracy of the model's predictions
D) A regularization parameter

4. In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?

A) To compare models' performance in terms of sensitivity and specificity
B) To measure feature importance
C) To visualize data distribution
D) To evaluate the mean squared error of a model

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

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

Solutions: