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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Scoring and Deployment | 20% | - Model scoring - Model deployment |
| Topic 2: Data Preparation and Exploration | 20% | - Data exploration using SAS Visual Statistics - Data quality - Importing data |
| Topic 3: Building Predictive Models | 40% | - Gradient boosting - Neural networks - Decision trees - Regression models |
| Topic 4: Model Assessment and Selection | 20% | - Model fit statistics - ROC and Lift curves - Model comparison |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
When setting proper inputs for the k-means algorithm, what parameter represents the number of clusters to create?
- A. K-value
- B. Learning rate
- C. Random seed
- D. Cluster centroid initialization
Correct Answer: A 🗳️
What is the purpose of deriving a cluster ID variable in cluster analysis?
- A. To set parallel coordinate properties
- B. To create a scatter plot of data points
- C. To assign cluster labels to data points
- D. To calculate the distance between clusters
Correct Answer: C 🗳️
What is the purpose of implementing score code generated by SAS Visual Statistics?
- A. To evaluate the performance of the scoring code
- B. To calculate the p-values of predictor variables
- C. To assess the distribution of residuals in the model
- D. To apply the trained model to new data for predictions
Correct Answer: D 🗳️
How can predicted values be derived and described in terms of predicted probabilities in SAS Visual Statistics?
- A. By applying the link function to the linear predictor
- B. By calculating the mean of the predictor variables
- C. By summing the residuals of the model
- D. By fitting a linear regression model to the data
Correct Answer: A 🗳️
What information can you interpret from a Cluster Matrix?
- A. The cluster centroids
- B. The proximity or similarity between clusters
- C. The number of data points in each cluster
- D. The order of cluster creation
Correct Answer: A,B 🗳️
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