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SASInstitute A00-406 Exam Syllabus Topics:

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

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

A) A single decision tree will always be outperformed by a model based on an ensemble of trees.
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 gradient boosting algorithm, for all but the first iteration, the target is the residual from the previous decision tree model.
D) In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.

2. What is the main goal of data preprocessing in a machine learning pipeline?

A) To remove irrelevant features
B) To prepare the data for analysis and modeling
C) To visualize the data
D) To train the model

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

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

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

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

5. Which type of model is well-suited for solving classification problems when dealing with high- dimensional data, such as text?

A) Linear Regression
B) Support Vector Machine (SVM)
C) Random Forest
D) K-Means Clustering

Solutions: