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Free SASInstitute A00-406 Exam Question Practice Exams
NEW QUESTION # 51
Which statement is true regarding decision trees and models based on ensembles of trees?
- A. In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.
- B. In the gradient boosting algorithm, for all but the first iteration, the target is the residual from the previous decision tree model.
- 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. A single decision tree will always be outperformed by a model based on an ensemble of trees.
Answer: B
NEW QUESTION # 52
What is "model reevaluation" in the model deployment phase?
- A. The evaluation of data distribution
- B. The process of selecting features
- C. The periodic assessment of a deployed model's performance and potential retraining
- D. The process of data preprocessing
Answer: C
NEW QUESTION # 53
Which technique is commonly used for feature scaling or normalization in machine learning pipelines?
- A. Standardization
- B. One-Hot Encoding
- C. Decision Trees
- D. Principal Component Analysis (PCA)
Answer: A
NEW QUESTION # 54
When building a recommendation system, which type of filtering is based on the user's behavior and preferences?
- A. Matrix factorization
- B. Collaborative filtering
- C. Singular Value Decomposition (SVD)
- D. Content-based filtering
Answer: B
NEW QUESTION # 55
What is the primary purpose of model documentation in the model deployment phase?
- A. To provide information on the model's development, architecture, and usage
- B. To assess data quality
- C. To create synthetic data
- D. To evaluate the model's accuracy
Answer: A
NEW QUESTION # 56
Which of the following is a common source for external data in the context of business analytics?
- A. Intranet databases
- B. Company financial reports
- C. Employee records
- D. CRM data
Answer: B
NEW QUESTION # 57
In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?
- A. To evaluate the mean squared error of a model
- B. To visualize data distribution
- C. To measure feature importance
- D. To compare models' performance in terms of sensitivity and specificity
Answer: D
NEW QUESTION # 58
What is the primary role of a loss function in model training?
- A. To maximize the model's performance
- B. To visualize the data
- C. To measure the difference between predicted and actual values
- D. To assess the accuracy of the model
Answer: C
NEW QUESTION # 59
What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?
- A. They require minimal data preprocessing.
- B. They are simple and easy to interpret.
- C. They are not suitable for large datasets.
- D. They combine multiple models to improve predictive performance.
Answer: D
NEW QUESTION # 60
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 cut off value.
- C. F1 score is applicable to a model with a binary target.
- D. F1 score is calculated based on a depth value.
Answer: B,C
NEW QUESTION # 61
What does the term "bias" in machine learning refer to?
- A. A model's inability to generalize to new data
- B. Systematic errors that cause a model to consistently underpredict or overpredict
- C. The overall accuracy of a model
- D. The simplicity of a model
Answer: B
NEW QUESTION # 62
Which type of model is well-suited for solving classification problems when dealing with high- dimensional data, such as text?
- A. Support Vector Machine (SVM)
- B. Random Forest
- C. Linear Regression
- D. K-Means Clustering
Answer: A
NEW QUESTION # 63
What is the primary purpose of a supervised machine learning pipeline in SAS Viya?
- A. Data preprocessing and cleaning
- B. Data visualization
- C. Data storage and retrieval
- D. Model training and evaluation
Answer: D
NEW QUESTION # 64
A project has been created and a pipeline has been run in Model Studio.
Which project setting can you edit?
- A. Partition Data percentages
- B. Rules for model comparison statistic
- C. Event-based Sampling proportions
- D. Advisor Options for missing values
Answer: B
NEW QUESTION # 65
What is a common example of an external data source for an organization?
- A. Employee databases
- B. Internal emails
- C. Customer surveys
- D. Intranet portals
Answer: C
NEW QUESTION # 66
In a supervised machine learning pipeline, what is the purpose of the test data set?
- A. To validate the model's performance
- B. To train the machine learning model
- C. To evaluate the model's predictions
- D. To preprocess the data
Answer: A
NEW QUESTION # 67
In natural language processing, what does "stemming" involve?
- A. Creating new words to improve model performance
- B. Reducing words to their base or root form
- C. Grouping similar words together based on their meanings
- D. Converting text to numbers for model input
Answer: B
NEW QUESTION # 68
Which SAS Viya component is typically used for deploying and monitoring machine learning models in production?
- A. SAS Enterprise Miner
- B. SAS Model Manager
- C. SAS Data Loader
- D. SAS Visual Analytics
Answer: B
NEW QUESTION # 69
In the context of model deployment, what is "model compliance"?
- A. The model's simplicity
- B. The degree to which the model adheres to regulatory or ethical guidelines
- C. The process of feature selection
- D. The model's efficiency
Answer: B
NEW QUESTION # 70
Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?
- A. Regularization
- B. One-Hot Encoding
- C. Principal Component Analysis (PCA)
- D. Naive Bayes
Answer: A
NEW QUESTION # 71
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