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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions (Q14-Q19):

NEW QUESTION # 14
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 is too complex and overperforms.
C. Overfitting occurs when the model is too simple and underperforms.
D. Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.

Answer: D

NEW QUESTION # 15
Which metric is commonly used to evaluate the performance of a regression model?

A. F1 Score
B. Mean Absolute Error (MAE)
C. Confusion Matrix
D. Precision

Answer: B

NEW QUESTION # 16
What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?

A. They combine multiple models to improve predictive performance.
B. They are not suitable for large datasets.
C. They are simple and easy to interpret.
D. They require minimal data preprocessing.

Answer: A

NEW QUESTION # 17
What is "model versioning" in the context of model deployment?

A. The process of creating synthetic data
B. The process of training a model from scratch
C. The process of evaluating model performance
D. The practice of keeping track of different versions of a model to maintain reproducibility

Answer: D

NEW QUESTION # 18
In natural language processing (NLP), what is a common preprocessing step for text data before building models?

A. Standardization
B. Principal Component Analysis (PCA)
C. Tokenization
D. One-Hot Encoding

Answer: C

NEW QUESTION # 19
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