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

1. What is the difference between a classification problem and a regression problem in machine learning?

A) Classification is a type of regression problem.
B) There is no difference; the terms are used interchangeably.
C) Classification predicts categorical outcomes, while regression predicts numeric outcomes.
D) Regression predicts categorical outcomes, while classification predicts numeric outcomes.

2. Which statement is true regarding decision trees and models based on ensembles of trees?

A) In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.
B) A single decision tree will always be outperformed by a model based on an ensemble of trees.
C) In the gradient boosting algorithm, for all but the first iteration, the target is the residual from the previous decision tree model.
D) For a Forest model, the out-of-bag sample is simply the original validation data set from when the raw data partitioning took place.

3. Which algorithm is commonly used for decision-making tasks in classification models?

A) Linear Regression
B) K-Means
C) Decision Trees
D) Principal Component Analysis (PCA)

4. What is "model reevaluation" in the model deployment phase?

A) The periodic assessment of a deployed model's performance and potential retraining
B) The process of data preprocessing
C) The evaluation of data distribution
D) The process of selecting features

5. Which of the following is NOT a common data format for exchanging data between systems?

A) JSON (JavaScript Object Notation)
B) HTML (Hypertext Markup Language)
C) CSV (Comma-Separated Values)
D) SQL (Structured Query Language)

Solutions: