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

1. Which data source typically provides access to real-time financial market data?

A) Social media platforms
B) Weather stations
C) Online news websites
D) Stock market APIs

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

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

3. What is the purpose of cross-validation in model building and evaluation?

A) Generating synthetic data
B) Reducing the dataset size
C) Splitting the dataset into training and testing sets
D) Assessing the model's generalization performance

4. Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?

A) Learning rate
B) Max depth
C) Min samples split
D) Max features

5. In a machine learning pipeline, what is the purpose of cross-validation?

A) To evaluate the model's performance on new data
B) To visualize the data distribution
C) To train multiple models on different subsets of the data to assess generalization
D) To split the dataset into training and testing sets

Solutions: