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A00-406 Dumps Questions Study Exam Guide
NEW QUESTION # 25
In the context of data sources, what is ETL?
- A. Efficient Text Link
- B. Examine, Test, Log
- C. Execute, Terminate, Launch
- D. Extract, Transform, Load
Answer: D
NEW QUESTION # 26
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 depth value.
- C. F1 score is calculated based on a cut off value.
- D. F1 score is applicable to a model with an interval target.
Answer: A,C
NEW QUESTION # 27
In model assessment, what does "cross-validation" aim to address?
- A. Model deployment
- B. Training a model
- C. Overfitting and generalization
- D. Data preprocessing
Answer: C
NEW QUESTION # 28
What does the term "bagging" refer to in ensemble learning?
- A. A form of dimensionality reduction
- B. A technique that reduces model complexity
- C. A type of feature extraction
- D. The process of combining multiple identical models to reduce variance
Answer: D
NEW QUESTION # 29
Refer to the treemap shown in the exhibit below:
Which statement is true about the tree map for a decision tree with a binary target?
- A. The top bar represents the node with the highest count.
- B. The darker bars represent nodes with a lower probability of event.
- C. The top bar represents the node with the highest probability of event.
- D. The wider bars represent nodes with a higher probability of event.
Answer: A
NEW QUESTION # 30
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 compare models' performance in terms of sensitivity and specificity
- C. To measure feature importance
- D. To visualize data distribution
Answer: B
NEW QUESTION # 31
In the context of data integration, what does "data transformation" refer to?
- A. Storing data in a centralized repository
- B. Backing up data for disaster recovery
- C. Extracting data from source systems
- D. Converting and reshaping data to match the target schema
Answer: D
NEW QUESTION # 32
What does the term "bias" in machine learning refer to?
- A. The overall accuracy of a model
- B. The simplicity of a model
- C. A model's inability to generalize to new data
- D. Systematic errors that cause a model to consistently underpredict or overpredict
Answer: D
NEW QUESTION # 33
What is the primary difference between supervised and unsupervised learning in model building?
- A. The presence or absence of a target variable
- B. The amount of labeled data required
- C. The type of data used
- D. The use of feature engineering
Answer: A
NEW QUESTION # 34
Which type of model is well-suited for solving classification problems when dealing with high- dimensional data, such as text?
- A. K-Means Clustering
- B. Random Forest
- C. Linear Regression
- D. Support Vector Machine (SVM)
Answer: D
NEW QUESTION # 35
What does API stand for in the context of data sources?
- A. Application Programming Interface
- B. Advanced Programming Integration
- C. Automated Program Integration
- D. Application Program Interface
Answer: A
NEW QUESTION # 36
In natural language processing (NLP), what is a common preprocessing step for text data before building models?
- A. Standardization
- B. Tokenization
- C. One-Hot Encoding
- D. Principal Component Analysis (PCA)
Answer: B
NEW QUESTION # 37
In model assessment, what is the purpose of feature importance analysis?
- A. To assess data quality
- B. To evaluate the significance of input features in making predictions
- C. To visualize data distribution
- D. To create synthetic features
Answer: B
NEW QUESTION # 38
What is feature engineering in the context of machine learning pipelines?
- A. Applying the model to new data
- B. Creating new features from existing data
- C. Building a machine learning model from scratch
- D. Testing the model's performance
Answer: B
NEW QUESTION # 39
What is the primary purpose of a supervised machine learning pipeline in SAS Viya?
- A. Data visualization
- B. Data preprocessing and cleaning
- C. Data storage and retrieval
- D. Model training and evaluation
Answer: D
NEW QUESTION # 40
Which of the following is a common source for external data in the context of business analytics?
- A. Intranet databases
- B. Employee records
- C. CRM data
- D. Company financial reports
Answer: D
NEW QUESTION # 41
What is "model reevaluation" in the model deployment phase?
- A. The periodic assessment of a deployed model's performance and potential retraining
- B. The evaluation of data distribution
- C. The process of selecting features
- D. The process of data preprocessing
Answer: A
NEW QUESTION # 42
What is the primary function of a data catalog in managing data sources?
- A. Data visualization
- B. Data documentation and discovery
- C. Data storage
- D. Data analysis
Answer: B
NEW QUESTION # 43
Which of the following best describes unstructured data?
- A. Data that is organized in rows and columns
- B. Data stored in a relational database
- C. Data with a clear schema
- D. Data that is difficult to process and lacks a predefined structure
Answer: D
NEW QUESTION # 44
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 create synthetic data
- C. To assess data quality
- D. To evaluate the model's accuracy
Answer: A
NEW QUESTION # 45
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