The Best SASInstitute A00-406 Study Guides and Dumps of 2025
Top SASInstitute A00-406 Exam Audio Study Guide! Practice Questions Edition
NEW QUESTION # 25
Which type of model is typically used for time-series forecasting?
- A. Decision Trees
- B. Logistic Regression
- C. AutoRegressive Integrated Moving Average (ARIMA)
- D. K-Means Clustering
Answer: C
NEW QUESTION # 26
What does "feature selection" refer to in the context of model building?
- A. The visualization of data distribution
- B. The evaluation of model accuracy
- C. The process of choosing the most relevant variables (features) for the model
- D. The creation of synthetic features from existing data
Answer: C
NEW QUESTION # 27
What does "data lineage" refer to in the context of data source management?
- A. The physical location of data storage
- B. The security protocols for data access
- C. The structure of a relational database
- D. The history of data transformation processes
Answer: D
NEW QUESTION # 28
When deploying a model, what is "model explainability"?
- A. The simplicity of the model
- B. The capability to interpret and understand the model's decisions and predictions
- C. The time it takes to make predictions
- D. The process of data preprocessing
Answer: B
NEW QUESTION # 29
What is metadata in the context of data sources?
- A. Data that is encrypted for security
- B. Data about data, providing information such as data source, structure, and context
- C. Data that is stored in a physical format
- D. Data that is in a non-standard, proprietary format
Answer: B
NEW QUESTION # 30
In the context of data sources, what is meant by data versioning?
- A. Keeping track of different versions or changes to data over time
- B. Storing multiple copies of the same data to increase redundancy
- C. Compressing data to reduce storage space
- D. Encrypting data to protect against unauthorized access
Answer: A
NEW QUESTION # 31
What does the term "bagging" refer to in ensemble learning?
- A. A technique that reduces model complexity
- B. The process of combining multiple identical models to reduce variance
- C. A form of dimensionality reduction
- D. A type of feature extraction
Answer: B
NEW QUESTION # 32
In natural language processing (NLP), what is a common preprocessing step for text data before building models?
- A. Tokenization
- B. Principal Component Analysis (PCA)
- C. Standardization
- D. One-Hot Encoding
Answer: A
NEW QUESTION # 33
What is the primary purpose of model deployment in the context of data science and machine learning?
- A. Model building
- B. Model evaluation
- C. Data preprocessing
- D. Making the model available for use in real-world applications
Answer: D
NEW QUESTION # 34
What is the purpose of an ROC curve (Receiver Operating Characteristic) in model assessment?
- A. To measure feature importance
- B. To compare a model's true positive rate with the false positive rate
- C. To visualize data distribution
- D. To evaluate regression models
Answer: B
NEW QUESTION # 35
Which statements are true for the F1 score?
(Choose 2.)
- A. F1 score is applicable to a model with a binary target.
- B. F1 score is calculated based on a cut off value.
- C. F1 score is calculated based on a depth value.
- D. F1 score is applicable to a model with an interval target.
Answer: A,B
NEW QUESTION # 36
When building a recommendation system, what does "collaborative filtering" rely on?
- A. The characteristics of the items being recommended
- B. Item-based clustering
- C. The popularity of items
- D. The past behavior or preferences of users
Answer: D
NEW QUESTION # 37
Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?
- A. Principal Component Analysis (PCA)
- B. Support Vector Machine (SVM)
- C. Linear Regression
- D. K-Means Clustering
Answer: B
NEW QUESTION # 38
What is the purpose of cross-entropy loss in machine learning, especially in the context of classification?
- A. To measure the dissimilarity between predicted and actual class probabilities
- B. To quantify the variance of a model
- C. To evaluate feature importance
- D. To calculate the mean squared error of a regression model
Answer: A
NEW QUESTION # 39
What is the primary objective of model validation during the model assessment phase?
- A. To assess the accuracy of the model
- B. To ensure the model generalizes well to new, unseen data
- C. To build a model from scratch
- D. To create synthetic data
Answer: B
NEW QUESTION # 40
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