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

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

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

2. When deploying a machine learning model, what is meant by "model latency"?

A) The time it takes to train a model
B) The time it takes to build a model
C) The time it takes to create synthetic data
D) The time it takes for the model to make predictions once deployed

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

4. In the context of model assessment, what does "bias" refer to?

A) A measure of the model's precision
B) The simplicity of the model
C) The process of feature engineering
D) A systematic error that causes a model to consistently overpredict

5. In a supervised learning pipeline, what is the role of the training data set?

A) To evaluate the model's predictions
B) To train the machine learning model
C) To test the model's generalization capability
D) To validate the model's performance

Solutions: