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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Evaluation and Deployment | - Model assessment metrics
|
| Topic 2: Data Preparation for Machine Learning | - Data cleaning and preprocessing
|
| Topic 3: Supervised Machine Learning Models | - Regression and classification models
|
| Topic 4: Machine Learning Pipelines in SAS Viya | - Pipeline construction
|
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
In natural language processing (NLP), what is a common preprocessing step for text data before building models?
- A. Standardization
- B. Principal Component Analysis (PCA)
- C. One-Hot Encoding
- D. Tokenization
Correct Answer: D 🗳️
What is the purpose of cross-validation in model building and evaluation?
- A. Reducing the dataset size
- B. Assessing the model's generalization performance
- C. Splitting the dataset into training and testing sets
- D. Generating synthetic data
Correct Answer: B 🗳️
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
Correct Answer: D 🗳️
What is the purpose of a confusion matrix in the context of classification models?
- A. To visualize the data
- B. To compute the mean squared error
- C. To evaluate model performance, especially for binary classification
- D. To summarize the distribution of target variables
Correct Answer: C 🗳️
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)
Correct Answer: D 🗳️
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