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SASInstitute A00-406 Exam Syllabus Topics:

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

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

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

2. What is the primary objective of model evaluation in the context of building predictive models?

A) Visualizing data
B) Assessing the model's performance and accuracy
C) Discovering patterns in data
D) Cleaning the data

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) 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.

4. In natural language processing (NLP), what is a common preprocessing step for text data before building models?

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

5. When assessing a classification model, what is the confusion matrix used to measure?

A) Model accuracy
B) Precision and recall
C) Data distribution
D) Model complexity

Solutions: