1. Which of the following correctly describes the hierarchical organization of an analysis within SAS Enterprise Miner?
a. A project can contain one or more diagrams. A diagram is composed of multiple nodes. A node is composed of multiple process flows.
b. A project can contain one or more process flows. A process flow can contain one or more diagrams.
c. A project can contain only one diagram, which is composed of one process flow. A process flow can contain multiple nodes.
d. A project can contain one or more diagrams. A diagram can contain one or more process flows. A process flow contains multiple nodes.
2. Which of the following statements best describes a SAS Enterprise Miner data source?
a. A data source is a SAS table that is used in a SAS Enterprise Miner process flow.
b. A data source is a SAS table that has been modified so that it can be used in a SAS Enterprise Miner project.
c. A data source is a metadata definition that is used in a SAS Enterprise Miner process flow to inform SAS Enterprise Miner only of the location of the SAS table.
d. A data source is a metadata definition that informs SAS Enterprise Miner about the name and location of a SAS table, the SAS code that is used to define a library path, and the variable roles, measurement levels, and other attributes that are important for the data mining project.
3. SAS Enterprise Miner stopping rules help to avoid which of the following:
a. logworth
b. orphan nodes
c. missing values
d. probability
4. Decision Tree models use pruning to adjust model complexity and avoid the potential problem known as what?
a. overfitting
b. accuracy
c. concordance
d. misclassification
5. The best split for an input is a split that yields what?
a. a maximal tree
b. a contingency table
c. a depth adjustment
d. the highest logworth
6. Which type of data set is used to monitor and tune a predictive model?
a. training
b. validation
c. testing
d. score
7. Which of the following is an essential task for any predictive model?
a. predict new cases
b. select useful inputs
c. optimize complexity
d. all of the above
8. Which partitioning strategy results in more stable predictive models?
a. devote more data to training and less data to validation
b. devote more data to validation and less data to training
c. devote more data to testing and less data to validation
d. devote more data to scoring and less data to training
9. What is odds? What is the difference between odds and probability?