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To prepare for the SASInstitute A00-255 certification exam, candidates can take advantage of various training resources offered by SAS, including e-learning courses, instructor-led training, and practice exams. Candidates can also use third-party study materials, such as books and online courses, to supplement their preparation. With proper preparation and practice, candidates can increase their chances of passing the A00-255 certification exam and advancing their careers in data science and analytics.
SASInstitute A00-255 Exam covers a range of topics related to predictive modeling using SAS Enterprise Miner 14. These include data preparation, variable selection, model selection, model assessment, and model deployment. A00-255 exam also covers advanced topics such as ensemble modeling, time series modeling, and text mining. A00-255 exam is based on SAS Enterprise Miner 14, which is a powerful tool for data mining and predictive modeling.
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NEW QUESTION # 12
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
Which of the following variables was used in the decision tree model?
Response:
Answer: D
NEW QUESTION # 13
Refer to the exhibit:
What would be the decision threshold (probability cutoff) generated for this decision matrix. You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
Answer: B
NEW QUESTION # 14
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Which of the following variable(s) is (are) statistically significant at the 5% level in the selected model?
Response:
Answer: D
NEW QUESTION # 15
What is the average squared error in the training data?
Response:
Answer: B
NEW QUESTION # 16
Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
Compare the performance of the ensemble and the four models using average squared error in the validation data. Which is the best model in this comparison?
Response:
Answer: B
NEW QUESTION # 17
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