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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Machine Learning Pipelines in SAS Viya | - Pipeline construction
|
| Model Evaluation and Deployment | - Model deployment
|
| Supervised Machine Learning Models | - Regression and classification models
|
| Data Preparation for Machine Learning | - Data cleaning and preprocessing
|
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
1. In the context of model assessment, what does "bias" refer to?
A) A systematic error that causes a model to consistently overpredict
B) A measure of the model's precision
C) The process of feature engineering
D) The simplicity of the model
2. Which statement is true regarding decision trees and models based on ensembles of trees?
A) For a Forest model, the out-of-bag sample is simply the original validation data set from when the raw data partitioning took place.
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) In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.
3. Which type of model is commonly used for anomaly detection in datasets?
A) Decision Trees
B) Principal Component Analysis (PCA)
C) Clustering Models
D) Linear Regression
4. What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?
A) They combine multiple models to improve predictive performance.
B) They are simple and easy to interpret.
C) They are not suitable for large datasets.
D) They require minimal data preprocessing.
5. In the context of model building, what is the purpose of hyperparameter tuning?
A) Visualizing data
B) Optimizing the model's hyperparameters for better performance
C) Selecting the most important features
D) Training the model
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: B |
